v0.11.2

env installation fix
fix pack install 2 fix pip install & git install failed fix pack build 1 Update SKILL.md Update Skills Update registry for all param desc
2026-05-23 22:12:28 +00:00 · 2026-05-14 18:21:43 +08:00 · 2026-05-14 18:21:22 +08:00 · 2026-04-27 20:28:18 +08:00 · 2026-04-22 19:54:59 +08:00 · 2026-04-22 19:54:57 +08:00
27 changed files with 559 additions and 1428 deletions
--- a/.conda/base/recipe.yaml
+++ b/.conda/base/recipe.yaml
@@ -3,7 +3,7 @@

 package:
  name: unilabos
-  version: 0.11.3
+  version: 0.11.2

 source:
  path: ../../unilabos
@@ -54,7 +54,7 @@ requirements:
  - pymodbus
  - matplotlib
  - pylibftdi
-  - uni-lab::unilabos-env ==0.11.3
+  - uni-lab::unilabos-env ==0.11.2

 about:
  repository: https://github.com/deepmodeling/Uni-Lab-OS
--- a/.conda/environment/recipe.yaml
+++ b/.conda/environment/recipe.yaml
@@ -2,7 +2,7 @@

 package:
  name: unilabos-env
-  version: 0.11.3
+  version: 0.11.2

 build:
  noarch: generic
--- a/.conda/full/recipe.yaml
+++ b/.conda/full/recipe.yaml
@@ -3,7 +3,7 @@

 package:
  name: unilabos-full
-  version: 0.11.3
+  version: 0.11.2

 build:
  noarch: generic
@@ -11,7 +11,7 @@ build:
 requirements:
  run:
  # Base unilabos package (includes unilabos-env)
-  - uni-lab::unilabos ==0.11.3
+  - uni-lab::unilabos ==0.11.2
  # Documentation tools
  - sphinx
  - sphinx_rtd_theme
--- a/.cursor/skills/add-device/SKILL.md
+++ b/.cursor/skills/add-device/SKILL.md
@@ -5,98 +5,9 @@ description: Guide for adding new devices to Uni-Lab-OS (接入新设备). Uses

 # 添加新设备到 Uni-Lab-OS

-本 Skill 是自包含的设备接入指南，不依赖外部文档。迁移给别人时，只复制 `.cursor/skills/add-device/SKILL.md` 即可获得核心规则、模板、验证方式和常见错误清单。
+**第一步：** 使用 Read 工具读取 `docs/ai_guides/add_device.md`，获取完整的设备接入指南。

-开始实现前，仍应搜索 `unilabos/devices/` 获取同类别已有设备的接口、参数名、状态字符串和返回值风格作为参考。
-
---
-
-## 接入工作流
-
-按下面顺序推进，并在工作中维护进度：
-
-```text
-设备接入进度：
- [ ] 1. 确定设备类别（物模型）和对外单位
- [ ] 2. 确定通信协议
- [ ] 3. 收集指令协议（SDK、厂商文档、寄存器表、HTTP API、用户口述）
- [ ] 4. 对齐同类设备接口（搜索 unilabos/devices/）
- [ ] 5. 创建驱动 unilabos/devices/<category>/<file>.py
- [ ] 6. 验证可导入、注册表扫描、启动测试
- [ ] 7. 如需要，配置实验图文件
-```
-
-## 设备类别（物模型）
-
-优先使用已有类别。只有确实无法归类时才使用 `custom`。
-
-| 类别 ID | 说明 | 标准属性 | 标准动作 |
-|---|---|---|---|
-| `temperature` | 加热、冷却、温控 | `temp`, `temp_target`, `status` | `set_temperature`, `stop` |
-| `pump_and_valve` | 泵、阀门、注射器 | 见子类型表 | 见子类型表 |
-| `motor` | 电机、步进马达 | `position`, `status` | `enable`, `move_position`, `move_speed`, `stop` |
-| `heaterstirrer` | 加热搅拌一体机 | `temp`, `stir_speed`, `status` | `set_temperature`, `stir`, `stop` |
-| `balance` | 天平、称重 | `weight`, `unit`, `status` | `tare`, `read_weight` |
-| `sensor` | 传感器（液位、温度等） | `value`, `level`, `status` | `read_value`, `set_threshold` |
-| `liquid_handling` | 液体处理机器人 | `status`, `deck_state` | `transfer_liquid`, `aspirate`, `dispense` |
-| `robot_arm` | 机械臂 | `arm_pose`, `arm_status` | `moveit_task`, `pick_and_place` |
-| `workstation` | 工作站、组合设备 | `workflow_sequence`, `material_info` | `create_order`, `scheduler_start`, `scheduler_stop` |
-| `virtual` | 虚拟、模拟设备 | 按模拟的真实设备定义 | 按模拟的真实设备定义 |
-| `custom` | 不属于以上类别 | 用户自定义 | 用户自定义 |
-
-`pump_and_valve` 子类型：
-
-| 子类型 | 最小通用属性 | 最小通用动作 | 单位约定 |
-|---|---|---|---|
-| 注射泵（syringe pump） | `status`, `valve_position`, `position` | `initialize`, `set_valve_position`, `set_position`, `pull_plunger`, `push_plunger`, `stop_operation` | 体积=mL, 速度=mL/s |
-| 电磁阀（solenoid valve） | `status`, `valve_position` | `open`, `close`, `set_valve_position` | 无 |
-| 蠕动泵（peristaltic pump） | `status`, `speed` | `start`, `stop`, `set_speed` | 流速=mL/min |
-
-对外暴露的属性和动作参数必须使用用户友好的物理单位（mL、ul、degC、RPM 等），硬件原始值转换放在驱动内部。
-
-## 通信协议和指令来源
-
-先确认通信方式，再确认具体指令协议。物模型只定义设备“应该做什么”，不会告诉你硬件“具体发什么字节/请求”。
-
-| 协议 | 常用 config 参数 | 常用依赖 | 现有抽象 |
-|---|---|---|---|
-| Serial (RS232/RS485) | `port`, `baudrate`, `timeout` | `pyserial` | 直接使用 `serial.Serial` |
-| Modbus RTU | `port`, `baudrate`, `slave_id` | `pymodbus` | `device_comms/modbus_plc/` |
-| Modbus TCP | `host`, `port`, `slave_id` | `pymodbus` | `device_comms/modbus_plc/` |
-| TCP Socket | `host`, `port`, `timeout` | stdlib | 直接使用 `socket` |
-| HTTP API | `url`, `token`, `timeout` | `requests` | `device_comms/rpc.py` |
-| OPC UA | `url` | `opcua` | `device_comms/opcua_client/` |
-| 无通信（虚拟） | 无 | 无 | 在动作中模拟行为 |
-
-必须从以下来源之一获得指令细节：
-
-| 来源 | 处理方式 |
-|---|---|
-| 现成 SDK/驱动代码 | 读取代码，提取指令逻辑，包装进 Uni-Lab-OS 类 |
-| 协议文档/手册 | 解析命令、响应、校验、寄存器、错误码 |
-| 用户口述 | 按描述实现指令编解码，标出不确定点 |
-| 标准协议 | 使用标准实现，例如 Modbus 寄存器表、SCPI |
-| 虚拟设备 | 跳过硬件通信，在动作方法中维护模拟状态 |
-
-## 对齐已有实现（强制）
-
-实现前必须搜索 `unilabos/devices/` 中同类别设备：
-
- 参数名必须与已有设备保持一致；动作方法参数名是接口契约，不要随意改成 `volume_ml`、`target_temp_c` 这类新名字。
- `status` 字符串值要和同类设备一致，优先使用英文稳定值，例如 `Idle`、`Running`、`Error`。
- 状态属性用 `@property` + `@topic_config()` 明确声明。
- 返回值使用结构化 dict，至少包含 `success`，需要给前端展示的信息放在 `message`、`data`、`error` 等字段。
-
-## 架构选择
-
-| 场景 | 推荐方式 |
-|---|---|
-| 简单设备 | 纯 Python 类 + `@device` |
-| 工作站/组合设备 | `WorkstationBase` 或项目内已有工作站模式 |
-| 液体处理 | `LiquidHandlerAbstract` / PyLabRobot 相关模式 |
-| Modbus 设备 | 复用 `device_comms/modbus_plc/` 或项目内 Modbus 示例 |
-| OPC UA 设备 | 复用 `device_comms/opcua_client/` |
-| 外部独立包 | 使用 `create-device-package` skill |
+该指南包含设备类别（物模型）列表、通信协议模板、常见错误检查清单等。搜索 `unilabos/devices/` 获取已有设备的实现参考。

 ---

@@ -176,29 +87,6 @@ Args:
 - 如果只写 `param: 参数说明`，`title` 会兜底为字段名，`description` 使用参数说明。
 - 如果没有写参数文档，生成器也会兜底补齐 `title=<字段名>` 和 `description=""`，但新设备应优先写清楚显示名和说明。

-### 特殊参数类型：ResourceSlot / DeviceSlot
-
-需要前端选择资源或设备时，用特殊类型注解，registry 会自动生成 `placeholder_keys`：
-
-```python
-from typing import List
-from unilabos.registry.placeholder_type import DeviceSlot, ResourceSlot
-
-@action(description="转移液体")
-def transfer(self, source: ResourceSlot, target: ResourceSlot, volume_ul: float) -> dict:
-    """
-    Args:
-        source[源资源]: 源容器或孔位。
-        target[目标资源]: 目标容器或孔位。
-        volume_ul[体积(ul)]: 转移体积。
-    """
-    return {"success": True}
-
-@action(description="同步设备")
-def sync_devices(self, devices: List[DeviceSlot]) -> dict:
-    return {"success": True, "count": len(devices)}
-```
-
 ### @topic_config — 状态属性配置

 ```python
@@ -306,154 +194,3 @@ class MyDevice:
 - `post_init` 用 `@not_action` 标记，参数类型标注为 `BaseROS2DeviceNode`
 - 运行时状态存储在 `self.data` 字典中
 - 设备文件放在 `unilabos/devices/<category>/` 目录下
-
---
-
-## 通信实现片段
-
-Serial 文本指令：
-
-```python
-def _send_command(self, cmd: str) -> str:
-    self.ser.write(f"{cmd}\r\n".encode())
-    return self.ser.readline().decode().strip()
-```
-
-RS-485 响应解析要先定位帧头，不要用硬编码索引直接解析原始响应：
-
-```python
-def _normalize_response(self, raw: str, start_marker: str = "/") -> str:
-    pos = raw.find(start_marker)
-    return raw[pos:] if pos >= 0 else raw
-```
-
-自定义二进制帧：
-
-```python
-def _build_frame(self, func_code: int, data: bytes) -> bytes:
-    frame = bytearray([0xFE, func_code]) + bytearray(data)
-    checksum = sum(frame[1:]) % 256
-    frame.append(checksum)
-    return bytes(frame)
-```
-
-Modbus 寄存器映射：
-
-```python
-REGISTER_MAP = {
-    "temp_target": {"addr": 0x000B, "scale": 10},
-}
-
-def set_temperature(self, temp: float, **kwargs) -> bool:
-    reg = REGISTER_MAP["temp_target"]
-    value = int(float(temp) * reg["scale"]) & 0xFFFF
-    self.client.write_register(reg["addr"], value, slave=self.slave_id)
-    self.data["temp_target"] = temp
-    return True
-```
-
-HTTP API 映射：
-
-```python
-API_MAP = {
-    "set_temperature": {
-        "method": "POST",
-        "endpoint": "/api/temperature",
-        "body_key": "target",
-    },
-}
-```
-
-SDK 封装：
-
-```python
-from my_device_sdk import DeviceController
-
-class MyDevice:
-    def __init__(self, device_id=None, config=None, **kwargs):
-        self.config = config or {}
-        self.controller = DeviceController(port=self.config.get("port", "COM1"))
-```
-
---
-
-## 验证
-
-无需手写注册表 YAML。`@device` 装饰器 + AST 扫描会在启动或检查时生成注册表条目。
-
-```bash
-# 1. 模块可导入
-python -c "from unilabos.devices.<category>.<file> import <ClassName>"
-
-# 2. 启动测试
-unilab -g <graph>.json
-
-# 3. 仅检查注册表
-unilab --check_mode --skip_env_check
-```
-
-仅在旧代码无 `@device`、需要覆盖特殊字段、或做 `--complete_registry` 旧设备补全时，才考虑 YAML。新设备默认不要手写 YAML。
-
-## 图文件节点模板
-
-实验图 JSON 中的 `class` 对应 `@device(id=...)`，`config` 会传入 `__init__` 的 `config` 字典：
-
-```json
-{
-  "id": "my_device_1",
-  "name": "我的设备",
-  "children": [],
-  "parent": null,
-  "type": "device",
-  "class": "my_device",
-  "position": {"x": 0, "y": 0, "z": 0},
-  "config": {
-    "port": "/dev/ttyUSB0",
-    "baudrate": 9600
-  },
-  "data": {}
-}
-```
-
-工作站需要同时配置 `deck` 和 `children`：
-
-```json
-{
-  "nodes": [
-    {
-      "id": "my_station",
-      "type": "device",
-      "class": "my_workstation",
-      "children": ["my_deck"],
-      "config": {},
-      "deck": {
-        "data": {
-          "_resource_child_name": "my_deck",
-          "_resource_type": "unilabos.resources.my_module:MyDeck"
-        }
-      }
-    },
-    {
-      "id": "my_deck",
-      "type": "deck",
-      "class": "MyDeckClass",
-      "parent": "my_station",
-      "config": {"type": "MyDeckClass", "setup": true}
-    }
-  ]
-}
-```
-
---
-
-## 常见错误清单
-
- 缺少 `@device`：设备不会被 AST 扫描发现。
- 只有 `@property` 没有 `@topic_config()`：属性不会稳定广播到 `status_types`。
- `post_init` 没有 `@not_action`：会被误暴露为动作。
- `self.data = {}`：空字典会导致属性读取和 schema 初始数据不稳定，必须预填充每个状态键。
- 动作参数重命名：不要把同类设备已有的 `volume` 改成 `volume_ml`，参数名是接口契约。
- `status` 使用中文或临时文本：前端和工作流依赖稳定英文状态值。
- async 方法中使用 `time.sleep()`：应使用 `await self._ros_node.sleep(seconds)`。
- 硬编码串口响应索引：RS-485 响应前可能有噪声字节，应先定位帧头。
- 把硬件寄存器单位暴露给用户：对外使用物理单位，驱动内部做 scale 转换。
--- a/.cursor/skills/virtual-workbench/SKILL.md
+++ b/.cursor/skills/virtual-workbench/SKILL.md
@@ -10,8 +10,7 @@ description: Operate Virtual Workbench via REST API — prepare materials, move
 - **device_id**: `virtual_workbench`
 - **Python 源码**: `unilabos/devices/virtual/workbench.py`
 - **设备类**: `VirtualWorkbench`
- **当前纳入动作**: 5 个（`auto-prepare_materials`, `auto-move_to_heating_station`, `auto-start_heating`, `auto-move_to_output`, `transfer`）
- **暂跳过动作**: `manual_confirm`、扣电测试 `test`（需要启用时先从最新注册表重新提取 schema）
+- **动作数**: 6（`auto-prepare_materials`, `auto-move_to_heating_station`, `auto-start_heating`, `auto-move_to_output`, `transfer`, `manual_confirm`）
 - **设备描述**: 模拟工作台，包含 1 个机械臂（每次操作 2s，独占锁）和 3 个加热台（每次加热 60s，可并行）

 ### 典型工作流程
@@ -152,8 +151,7 @@ curl -s -X POST "$BASE/api/v1/lab/mcp/run/action" \
 | `auto-start_heating` | `UniLabJsonCommand` |
 | `auto-move_to_output` | `UniLabJsonCommand` |
 | `transfer` | `UniLabJsonCommandAsync` |
-
-> `manual_confirm` 和扣电测试 `test` 当前不纳入本 skill 的推荐操作范围；不要基于历史 JSON 直接调用，需先重新生成并校验 schema。
+| `manual_confirm` | `UniLabJsonCommand` |

 ### 10. 查询任务状态

@@ -227,9 +225,11 @@ curl -s -X PUT "$BASE/api/v1/edge/material/node" \
 | `transfer`        | `resource`       | ResourceSlot | 待转移物料数组       |
 | `transfer`        | `target_device`  | DeviceSlot   | 目标设备路径         |
 | `transfer`        | `mount_resource` | ResourceSlot | 目标孔位数组         |
+| `manual_confirm`  | `resource`       | ResourceSlot | 确认用物料数组       |
+| `manual_confirm`  | `target_device`  | DeviceSlot   | 确认用目标设备       |
+| `manual_confirm`  | `mount_resource` | ResourceSlot | 确认用目标孔位数组   |

 > `prepare_materials`、`move_to_heating_station`、`start_heating`、`move_to_output` 这 4 个动作**无 Slot 字段**，参数为纯数值/整数。
-> `manual_confirm` 先跳过，不维护其 Slot 字段表。

 ---

@@ -270,13 +270,3 @@ prepare_materials (count=5)
 ```

 创建节点时，`prepare_materials` 的 5 个 output handle（`channel_1` ~ `channel_5`）分别连接到 5 个 `move_to_heating_station` 节点的 `material_input` handle。每个 `move_to_heating_station` 的 `heating_station_output` 和 `material_number_output` 连接到对应 `start_heating` 的 `station_id_input` 和 `material_number_input`。
-
-`start_heating` 完成后还需要继续连接到 `move_to_output`，否则加热完成的物料不会移出加热台：
-
-| source action | source handle | target action | target handle | 传递参数 |
-| ------------- | ------------- | ------------- | ------------- | -------- |
-| `auto-prepare_materials` | `channel_N` | `auto-move_to_heating_station` | `material_input` | `material_number` |
-| `auto-move_to_heating_station` | `heating_station_output` | `auto-start_heating` | `station_id_input` | `station_id` |
-| `auto-move_to_heating_station` | `material_number_output` | `auto-start_heating` | `material_number_input` | `material_number` |
-| `auto-start_heating` | `heating_done_station` | `auto-move_to_output` | `output_station_input` | `station_id` |
-| `auto-start_heating` | `heating_done_material` | `auto-move_to_output` | `output_material_input` | `material_number` |
--- a/.cursor/skills/virtual-workbench/action-index.md
+++ b/.cursor/skills/virtual-workbench/action-index.md
@@ -1,8 +1,6 @@
 # Action Index — virtual_workbench

-当前纳入 5 个动作，按功能分类。每个动作的完整 JSON Schema 在 `actions/<name>.json`。
-
-暂跳过：`manual_confirm`、扣电测试 `test`。这两个动作需要启用时，先从最新 `req_device_registry_upload.json` 重新提取 schema 并校验参数。
+6 个动作，按功能分类。每个动作的完整 JSON Schema 在 `actions/<name>.json`。

 ---

@@ -62,18 +60,17 @@

 ---

-## 暂跳过动作
+## 人工确认

 ### `manual_confirm`

-创建人工确认节点，等待用户手动确认后继续（含物料转移上下文）。当前先不纳入推荐操作范围。
+创建人工确认节点，等待用户手动确认后继续（含物料转移上下文）

 - **action_type**: `UniLabJsonCommand`
 - **Schema**: [`actions/manual_confirm.json`](actions/manual_confirm.json)
- **状态**: 暂跳过。源码参数已包含扣电测试相关字段，历史 JSON 可能过期；需要启用时重新提取 schema。
-
-### `test`
-
-启动扣电测试。当前先不纳入本 skill。
-
- **状态**: 暂跳过。需要启用时从注册表生成 `actions/test.json` 后再补充索引。
+- **核心参数**: `resource`, `target_device`, `mount_resource`, `timeout_seconds`, `assignee_user_ids`
+- **占位符字段**:
+  - `resource` — **ResourceSlot**，物料数组
+  - `target_device` — **DeviceSlot**，目标设备路径
+  - `mount_resource` — **ResourceSlot**，目标孔位数组
+  - `assignee_user_ids` — `unilabos_manual_confirm` 类型
--- a/.github/workflows/ci-check.yml
+++ b/.github/workflows/ci-check.yml
@@ -25,7 +25,7 @@ jobs:
          fetch-depth: 0

      - name: Setup Miniforge
-        uses: conda-incubator/setup-miniconda@v4
+        uses: conda-incubator/setup-miniconda@v3
        with:
          miniforge-version: latest
          use-mamba: true
--- a/.github/workflows/conda-pack-build.yml
+++ b/.github/workflows/conda-pack-build.yml
@@ -43,7 +43,7 @@ jobs:
            platform: linux-64
            env_file: unilabos-linux-64.yaml
            script_ext: sh
-          - os: macos-15-intel # Intel x86_64
+          - os: macos-15 # Intel (via Rosetta)
            platform: osx-64
            env_file: unilabos-osx-64.yaml
            script_ext: sh
@@ -86,7 +86,7 @@ jobs:

      - name: Setup Miniforge (with mamba)
        if: steps.should_build.outputs.should_build == 'true'
-        uses: conda-incubator/setup-miniconda@v4
+        uses: conda-incubator/setup-miniconda@v3
        with:
          miniforge-version: latest
          use-mamba: true
--- a/.github/workflows/deploy-docs.yml
+++ b/.github/workflows/deploy-docs.yml
@@ -51,7 +51,7 @@ jobs:
          fetch-depth: 0

      - name: Setup Miniforge (with mamba)
-        uses: conda-incubator/setup-miniconda@v4
+        uses: conda-incubator/setup-miniconda@v3
        with:
          miniforge-version: latest
          use-mamba: true
@@ -84,7 +84,7 @@ jobs:

      - name: Setup Pages
        id: pages
-        uses: actions/configure-pages@v6
+        uses: actions/configure-pages@v5
        if: |
          github.event.workflow_run.head_branch == 'main' ||
          (github.event_name == 'workflow_dispatch' && github.event.inputs.deploy_to_pages == 'true')
@@ -105,7 +105,7 @@ jobs:
          test -f docs/_build/html/index.html && echo "✓ index.html exists" || echo "✗ index.html missing"

      - name: Upload build artifacts
-        uses: actions/upload-pages-artifact@v5
+        uses: actions/upload-pages-artifact@v4
        if: |
          github.event.workflow_run.head_branch == 'main' ||
          (github.event_name == 'workflow_dispatch' && github.event.inputs.deploy_to_pages == 'true')
@@ -125,4 +125,4 @@ jobs:
    steps:
      - name: Deploy to GitHub Pages
        id: deployment
-        uses: actions/deploy-pages@v5
+        uses: actions/deploy-pages@v4
--- a/.github/workflows/multi-platform-build.yml
+++ b/.github/workflows/multi-platform-build.yml
@@ -63,7 +63,7 @@ jobs:
          - os: ubuntu-latest
            platform: linux-64
            env_file: unilabos-linux-64.yaml
-          - os: macos-15-intel # Intel x86_64
+          - os: macos-15 # Intel (via Rosetta)
            platform: osx-64
            env_file: unilabos-osx-64.yaml
          - os: macos-latest # ARM64
@@ -101,11 +101,10 @@ jobs:

      - name: Setup Miniforge
        if: steps.should_build.outputs.should_build == 'true'
-        uses: conda-incubator/setup-miniconda@v4
+        uses: conda-incubator/setup-miniconda@v3
        with:
          miniforge-version: latest
          use-mamba: true
-          python-version: '3.11.14'
          channels: conda-forge,robostack-staging
          channel-priority: strict
          activate-environment: build-env
@@ -115,22 +114,24 @@ jobs:
      - name: Install rattler-build and anaconda-client
        if: steps.should_build.outputs.should_build == 'true'
        run: |
-          mamba install -n build-env --override-channels -c conda-forge rattler-build anaconda-client -y
+          mamba install --override-channels -c conda-forge rattler-build anaconda-client -y

      - name: Show environment info
        if: steps.should_build.outputs.should_build == 'true'
        run: |
          conda info
-          conda list -n build-env | grep -E "(rattler-build|anaconda-client)"
-          conda run -n build-env rattler-build --version
-          conda run -n build-env anaconda --version
+          conda list | grep -E "(rattler-build|anaconda-client)"
          echo "Platform: ${{ matrix.platform }}"
          echo "OS: ${{ matrix.os }}"

      - name: Build conda package
        if: steps.should_build.outputs.should_build == 'true'
        run: |
-          conda run -n build-env rattler-build build -r ./recipes/msgs/recipe.yaml --target-platform ${{ matrix.platform }} -c robostack -c robostack-staging -c conda-forge
+          if [[ "${{ matrix.platform }}" == "osx-arm64" ]]; then
+            rattler-build build -r ./recipes/msgs/recipe.yaml -c robostack -c robostack-staging -c conda-forge
+          else
+            rattler-build build -r ./recipes/msgs/recipe.yaml -c robostack -c robostack-staging -c conda-forge
+          fi

      - name: List built packages
        if: steps.should_build.outputs.should_build == 'true'
@@ -170,5 +171,5 @@ jobs:
        run: |
          for package in $(find ./output -name "*.conda"); do
            echo "Uploading $package to unilab organization..."
-            conda run -n build-env anaconda -t ${{ secrets.ANACONDA_API_TOKEN }} upload --user uni-lab --force "$package"
+            anaconda -t ${{ secrets.ANACONDA_API_TOKEN }} upload --user uni-lab --force "$package"
          done
--- a/.github/workflows/unilabos-conda-build.yml
+++ b/.github/workflows/unilabos-conda-build.yml
@@ -59,7 +59,7 @@ jobs:
        include:
          - os: ubuntu-latest
            platform: linux-64
-          - os: macos-15-intel # Intel x86_64
+          - os: macos-15 # Intel (via Rosetta)
            platform: osx-64
          - os: macos-latest # ARM64
            platform: osx-arm64
@@ -94,11 +94,10 @@ jobs:

      - name: Setup Miniforge
        if: steps.should_build.outputs.should_build == 'true'
-        uses: conda-incubator/setup-miniconda@v4
+        uses: conda-incubator/setup-miniconda@v3
        with:
          miniforge-version: latest
          use-mamba: true
-          python-version: '3.11.14'
          channels: conda-forge,robostack-staging,uni-lab
          channel-priority: strict
          activate-environment: build-env
@@ -108,15 +107,13 @@ jobs:
      - name: Install rattler-build and anaconda-client
        if: steps.should_build.outputs.should_build == 'true'
        run: |
-          mamba install -n build-env --override-channels -c conda-forge rattler-build anaconda-client -y
+          mamba install --override-channels -c conda-forge rattler-build anaconda-client -y

      - name: Show environment info
        if: steps.should_build.outputs.should_build == 'true'
        run: |
          conda info
-          conda list -n build-env | grep -E "(rattler-build|anaconda-client)"
-          conda run -n build-env rattler-build --version
-          conda run -n build-env anaconda --version
+          conda list | grep -E "(rattler-build|anaconda-client)"
          echo "Platform: ${{ matrix.platform }}"
          echo "OS: ${{ matrix.os }}"
          echo "Build full package: ${{ github.event_name == 'workflow_dispatch' && github.event.inputs.build_full == 'true' }}"
@@ -131,7 +128,7 @@ jobs:
        if: steps.should_build.outputs.should_build == 'true'
        run: |
          echo "Building unilabos-env (conda environment dependencies)..."
-          conda run -n build-env rattler-build build -r .conda/environment/recipe.yaml --target-platform ${{ matrix.platform }} -c uni-lab -c robostack-staging -c conda-forge
+          rattler-build build -r .conda/environment/recipe.yaml -c uni-lab -c robostack-staging -c conda-forge

      - name: Upload unilabos-env to Anaconda.org (if enabled)
        if: |
@@ -143,7 +140,7 @@ jobs:
        run: |
          echo "Uploading unilabos-env to uni-lab organization..."
          for package in $(find ./output -name "unilabos-env*.conda"); do
-            conda run -n build-env anaconda -t ${{ secrets.ANACONDA_API_TOKEN }} upload --user uni-lab --force "$package"
+            anaconda -t ${{ secrets.ANACONDA_API_TOKEN }} upload --user uni-lab --force "$package"
          done

      - name: Build unilabos (with pip package)
@@ -151,7 +148,7 @@ jobs:
        run: |
          echo "Building unilabos package..."
          # 如果已上传到 Anaconda，从 uni-lab channel 获取 unilabos-env；否则从本地 output 获取
-          conda run -n build-env rattler-build build -r .conda/base/recipe.yaml --target-platform ${{ matrix.platform }} -c uni-lab -c robostack-staging -c conda-forge --channel ./output
+          rattler-build build -r .conda/base/recipe.yaml -c uni-lab -c robostack-staging -c conda-forge --channel ./output

      - name: Upload unilabos to Anaconda.org (if enabled)
        if: |
@@ -163,7 +160,7 @@ jobs:
        run: |
          echo "Uploading unilabos to uni-lab organization..."
          for package in $(find ./output -name "unilabos-0*.conda" -o -name "unilabos-[0-9]*.conda"); do
-            conda run -n build-env anaconda -t ${{ secrets.ANACONDA_API_TOKEN }} upload --user uni-lab --force "$package"
+            anaconda -t ${{ secrets.ANACONDA_API_TOKEN }} upload --user uni-lab --force "$package"
          done

      - name: Build unilabos-full - Only when explicitly requested
@@ -173,7 +170,7 @@ jobs:
          github.event.inputs.build_full == 'true'
        run: |
          echo "Building unilabos-full package on ${{ matrix.platform }}..."
-          conda run -n build-env rattler-build build -r .conda/full/recipe.yaml --target-platform ${{ matrix.platform }} -c uni-lab -c robostack-staging -c conda-forge --channel ./output
+          rattler-build build -r .conda/full/recipe.yaml -c uni-lab -c robostack-staging -c conda-forge --channel ./output

      - name: Upload unilabos-full to Anaconda.org (if enabled)
        if: |
@@ -184,7 +181,7 @@ jobs:
        run: |
          echo "Uploading unilabos-full to uni-lab organization..."
          for package in $(find ./output -name "unilabos-full*.conda"); do
-            conda run -n build-env anaconda -t ${{ secrets.ANACONDA_API_TOKEN }} upload --user uni-lab --force "$package"
+            anaconda -t ${{ secrets.ANACONDA_API_TOKEN }} upload --user uni-lab --force "$package"
          done

      - name: List built packages
--- a/docs/developer_guide/add_PLC.md
+++ b/docs/developer_guide/add_PLC.md
@@ -1,611 +0,0 @@
-# PLC 通信标准与设备驱动编写指南（基于 AI4M 工站）
-
-> 本文档以 `unilabos/devices/workstation/AI4M`（水凝胶检测工站）为参考实现，
-> 介绍如何将 PLC 控制的实验设备接入 Uni-Lab-OS：包含通信协议选型、节点表标准、
-> 通信基类、设备驱动、Registry 配置以及调试方法。
->
-> 阅读对象：负责现场调试与设备接入的同学。
-
---
-
-## 0. 总览：一台 PLC 设备从硬件到云端的链路
-
-```
-       PLC（西门子 / 倍福 / 三菱 / 汇川 / 国产 PLC ...）
-                   ▲
-                   │  各家 PLC 私有协议（S7 / Modbus / EtherCAT ...）
-                   │
-        ┌──────────┴──────────┐
-        │  OPC UA Server      │  ← 统一在 PLC 侧或独立网关上配置
-        │  （内置或 KEPServer）│
-        └──────────┬──────────┘
-                   │  OPC UA over TCP（标准协议）
-                   │
-        ┌──────────┴──────────┐
-        │  Uni-Lab 设备驱动    │  ← 本教程主体
-        │  AI4MDevice         │
-        │  ├─ base_opcua_client.py  通信基类
-        │  ├─ opcua_nodes_*.csv     节点表（标准）
-        │  └─ AI4M.py               动作函数
-        └──────────┬──────────┘
-                   │  ROS2 Action / 云端 HTTP
-                   ▼
-              实验记录本 / 云端调度
-```
-
-**统一约定**：所有 PLC 设备**只暴露 OPC UA 接口**给 Uni-Lab，PC 端不直接处理 S7 / Modbus 等底层协议。
-这是 Uni-Lab 在工站类设备上的 PLC 通信标准。
-
---
-
-## 1. 为什么选 OPC UA 作为标准？
-
-| 维度 | 自研 TCP/串口协议 | Modbus | **OPC UA** |
-|---|---|---|---|
-| 厂家无关 | ✗ | 部分 | **✓** |
-| 自带类型系统 | ✗ | ✗（裸寄存器） | **✓（Boolean/Int16/Float...）** |
-| 命名空间 / 节点树 | ✗ | ✗（地址=魔数） | **✓（带名字、可分组）** |
-| 订阅推送 | ✗ | ✗ | **✓（DataChange Notification）** |
-| 鉴权 / 加密 | 自己造 | ✗ | **✓** |
-| 与 PLC 工程师沟通成本 | 高 | 中 | **低（按变量名沟通）** |
-
-实际接入时，PLC 工程师只需要在 PLC 侧把约定的"上位通讯变量"暴露到 OPC UA Server，
-我们在 PC 侧就能用 `节点名 + 数据类型` 直接读写，不用管底层是 S7 还是 Modbus。
-
---
-
-## 2. 节点表标准：`opcua_nodes_xxx.csv`
-
-PLC 侧暴露的所有变量统一**用一张 CSV 表**描述，这是 PC 端和 PLC 端**唯一的接口契约**。
-位置示例：`unilabos/devices/workstation/AI4M/opcua_nodes_AI4M.csv`。
-
-### 2.1 列定义
-
-| 列名 | 是否必填 | 说明 |
-|---|---|---|
-| `Name` | ✅ | 节点名（PLC 工程师在 PLC 项目中真实使用的变量名，通常是中文/原始名） |
-| `EnglishName` | 推荐 | 英文别名，**PC 端代码全部用这个名字**调用 |
-| `NodeType` | ✅ | `VARIABLE`（变量）或 `METHOD`（方法），AI4M 全部用变量 |
-| `DataType` | ✅ | `BOOLEAN` / `INT16` / `INT32` / `FLOAT` / `DOUBLE` / `STRING` ... |
-| `NodeLanguage` | 推荐 | `Chinese` / `English`，配合 `EnglishName` 做映射 |
-| `NodeId` | ✅ | OPC UA 标准 NodeId，格式 `ns=<namespace>;s=<string>` 或 `ns=<n>;i=<int>` |
-
-### 2.2 真实样例（节选自 `opcua_nodes_AI4M.csv`）
-
-| Name | EnglishName | NodeType | DataType | NodeLanguage | NodeId |
-|---|---|---|---|---|---|
-| 机器人空闲 | `robot_ready` | VARIABLE | BOOLEAN | Chinese | `ns=4;s=上位通讯变量\|机器人空闲` |
-| 机器人取烧杯编号 | `robot_pick_beaker_id` | VARIABLE | INT16 | Chinese | `ns=4;s=上位通讯变量\|机器人取烧杯编号` |
-| 检测1请求参数 | `station_1_request_params` | VARIABLE | BOOLEAN | Chinese | `ns=4;s=上位通讯变量\|检测1请求参数` |
-| 检测1工艺完成 | `station_1_process_complete` | VARIABLE | BOOLEAN | Chinese | `ns=4;s=上位通讯变量\|检测1工艺完成` |
-| 磁力搅拌参数设置_C[0].搅拌速度 | `mag_stirrer_c0_stir_speed` | VARIABLE | INT16 | Chinese | `ns=4;s=上位通讯变量\|磁力搅拌参数设置_C[0].搅拌速度` |
-| 报警复位 | `alarm_reset` | VARIABLE | BOOLEAN | Chinese | `ns=4;s=上位通讯变量\|报警复位` |
-
-### 2.3 设计规范（必读）
-
-1. **命名按"角色-编号-属性"分层**，便于代码批量寻址：
-   - `mag_stirrer_c{0..4}_stir_speed`（搅拌仪 0~4 的搅拌速度）
-   - `station_{1..3}_process_complete`（检测站 1~3 的完成信号）
-   - `robot_rack_pick_beaker_{1..5}_complete`（取烧杯 1~5 的完成信号）
-
-   这样在驱动里可以直接 `f"mag_stirrer_c{idx}_stir_speed"` 拼出节点名。
-
-2. **数据类型与 PLC 侧严格一致**：
-   - `BOOL` → `BOOLEAN`，`INT/WORD` → `INT16/UINT16`，`DINT` → `INT32`，`REAL` → `FLOAT`。
-   - 类型不一致会触发 `BadTypeMismatch`，写入失败。
-
-3. **NodeId 必须从 PLC 工程或 OPC UA Server 中导出**，不要自己拼。
-   常见格式：
-   - 西门子 1500：`ns=4;s=上位通讯变量|<变量名>`
-   - 倍福 TwinCAT：`ns=4;s=PLC1.MAIN.<变量名>`
-   - KEPServerEX：`ns=2;s=Channel1.Device1.<Tag>`
-
-4. **每个工站一个独立 CSV**，不要共用。
-   AI4M 中真机用 `opcua_nodes_AI4M.csv`，仿真用 `opcua_nodes_AI4M_sim.csv`。
-
---
-
-## 3. 通信基类架构
-
-文件：`unilabos/devices/workstation/AI4M/base_opcua_client.py`
-
-整个通信层分两层：
-
-```
-BaseOpcUaClient                       # 最小可用：连接 + 节点注册 + 读写 + 方法调用
-        ▲
-        │ 继承
-        │
-OpcUaClientWithSubscription           # 生产可用：+ 订阅推送 + 缓存 + 自动重连
-        ▲
-        │ 继承
-        │
-AI4MDevice                            # 业务驱动：在它之上写设备动作函数
-```
-
-### 3.1 `BaseOpcUaClient` 核心能力
-
-```python
-class BaseOpcUaClient(UniversalDriver):
-    client: Optional[Client] = None
-    _node_registry: Dict[str, OpcUaNodeBase] = {}     # name -> Variable/Method
-    _name_mapping: Dict[str, str] = {}                # 英文名 -> 中文名
-    _reverse_mapping: Dict[str, str] = {}             # 中文名 -> 英文名
-    _found_node_objects: Dict[str, Any] = {}          # 缓存 ua.Node 用于订阅
-
-    @classmethod
-    def load_csv(cls, file_path) -> Tuple[List[OpcUaNode], dict, dict]: ...
-    def register_node_list(self, node_list) -> "BaseOpcUaClient": ...
-    def use_node(self, name) -> OpcUaNodeBase: ...
-    def read_node(self, node_name: str) -> str: ...   # 返回 JSON
-    def write_node(self, json_input: str) -> str: ...
-    def call_method(self, node_name, *args) -> Tuple[Any, bool]: ...
-```
-
-它做的事情可以归纳为四步：
-
-1. **`load_csv`**：读取节点表，建立 `Name ↔ EnglishName` 双向映射。
-2. **`register_node_list`**：把节点登记进 `_variables_to_find` 待查找列表。
-3. **`_connect` → `_find_nodes`**：连上 OPC UA 后，按 `NodeId` 把每个节点解析成 `Variable` / `Method` 对象，放进 `_node_registry`。
-4. **`use_node(name)`**：业务代码取节点的唯一入口，**支持中英文混用**，找不到会自动重试一次。
-
-### 3.2 `OpcUaClientWithSubscription` 增强能力
-
-在 `BaseOpcUaClient` 基础上提供三个生产环境必备的能力：
-
-#### a) 订阅缓存（高频读零开销）
-
-```python
-def _setup_subscriptions(self):
-    self._subscription = self.client.create_subscription(
-        self._subscription_interval,    # 默认 500ms
-        SubscriptionHandler(self),
-    )
-    for node_name, node in self._node_registry.items():
-        if node.type == NodeType.VARIABLE and node.node_id:
-            handle = self._subscription.subscribe_data_change(ua_node)
-            self._subscription_handles[node_name] = handle
-```
-
-当 PLC 侧变量变化时，`datachange_notification` 回调会把新值写进 `self._node_values[name]`，
-后续 `get_node_value` 优先读缓存——**业务代码可以放心地写 `while not self.get_node_value(...): time.sleep(1)` 而不用担心 OPC UA 频繁请求**。
-
-#### b) 智能缓存的 `get_node_value`
-
-```python
-def get_node_value(self, name, use_cache=True, force_read=False):
-    # 1. 中英文名归一化
-    chinese_name = self._name_mapping.get(name, name)
-
-    # 2. force_read=True 强制透传到 OPC UA Server
-    if force_read: ...
-
-    # 3. 命中订阅推送 → 直接返回缓存
-    # 4. 命中按需读 + 未过期（cache_timeout=5s）→ 返回缓存
-    # 5. 否则发起 read 并更新缓存
-```
-
-#### c) 连接监控 + 自动重连
-
-后台线程每 30s 调一次 `client.get_namespace_array()` 探活，断线则自动 `disconnect → connect → 重新订阅`，最多重试 5 次。
-
-### 3.3 数据类型 / 节点类型
-
-`unilabos/device_comms/opcua_client/node/uniopcua.py`：
-
-```python
-class DataType(Enum):
-    BOOLEAN = VariantType.Boolean
-    INT16   = VariantType.Int16
-    INT32   = VariantType.Int32
-    FLOAT   = VariantType.Float
-    STRING  = VariantType.String
-    # ...
-
-class NodeType(Enum):
-    VARIABLE = NodeClass.Variable
-    METHOD   = NodeClass.Method
-    OBJECT   = NodeClass.Object
-```
-
-`Variable.write()` 内部会按 `DataType` 做强制类型转换，
-所以 CSV 里的 `DataType` 列就是"PC 端转换写入值的类型说明书"。
-
---
-
-## 4. 编写设备驱动：以 `AI4MDevice` 为例
-
-文件：`unilabos/devices/workstation/AI4M/AI4M.py`
-
-### 4.1 继承通信基类，最小骨架
-
-```python
-from typing import Optional
-from unilabos.devices.workstation.AI4M.base_opcua_client import OpcUaClientWithSubscription
-
-class AI4MDevice(OpcUaClientWithSubscription):
-    def __init__(
-        self,
-        url: str,                              # opc.tcp://192.168.1.10:4840
-        deck: Optional[AI4M_deck] = None,      # 物料台面（资源树）
-        csv_path: str = None,                  # 节点表 CSV
-        username: str = None,
-        password: str = None,
-        use_subscription: bool = True,
-        cache_timeout: float = 5.0,
-        subscription_interval: int = 500,
-        *args, **kwargs,
-    ):
-        super().__init__(
-            url=url, username=username, password=password,
-            use_subscription=use_subscription,
-            cache_timeout=cache_timeout,
-            subscription_interval=subscription_interval,
-            *args, **kwargs,
-        )
-
-        # 物料台面初始化（见教程 4. 物料系统）
-        self.deck = deck or AI4M_deck(setup=True)
-        self._robot_lock = threading.Lock()
-
-        # 关键：加载节点表
-        if csv_path:
-            self.load_nodes_from_csv(csv_path)
-```
-
-`load_nodes_from_csv` 会一次性完成：解析 CSV → 注册节点 → 解析 NodeId → 建立订阅，
-**之后整个驱动都通过 `self.get_node_value(name)` / `self.set_node_value(name, value)` 操作 PLC**。
-
-### 4.2 PLC 通信的核心模式：握手协议（Handshake）
-
-PLC 编程的本质是"扫描周期 + 状态机"，PC 端**绝对不能用 fire-and-forget 的方式发指令**。
-和 PLC 配合的标准模式是 **"PC 写指令 → PC 等待 PLC 回执 → PC 复位指令"**。
-
-AI4M 中所有 `trigger_*` 函数都遵循以下三种握手范式之一：
-
-#### 范式 A：脉冲触发 + 完成信号（最常用）
-
-```python
-def trigger_init(self) -> dict:
-    # ① 复位上一轮残留
-    self.set_node_value("alarm_reset", True); time.sleep(1.0)
-    self.set_node_value("alarm_reset", False)
-    self.set_node_value("manual_auto_switch", False)
-
-    # ② 等待 PLC 退出自动模式
-    while self.get_node_value("auto_mode"):
-        time.sleep(1.0)
-
-    # ③ 发起初始化脉冲（True → False）
-    self.set_node_value("initialize", True); time.sleep(1.0)
-    self.set_node_value("initialize", False)
-
-    # ④ 等待 PLC 给出完成信号
-    while not self.get_node_value("init finished"):
-        time.sleep(1.0)
-
-    return {"message": "设备初始化完成"}
-```
-
-要点：
- **"PC 写一个 BOOL 拉高再拉低"** 模拟脉冲，PLC 用上升沿触发动作。
- **`get_node_value` 要在 while 循环里轮询**，配合订阅缓存基本无压力。
- **每个动作必须有"开始"和"完成"两个独立的 BOOL 节点**，不能复用。
-
-#### 范式 B：参数下发 + 请求/已执行/完成 三步握手（带数据的工艺）
-
-```python
-def trigger_station_process(self, station_id: int, mag_stir_speed: int, ...):
-    request_node        = f"station_{station_id}_request_params"
-    params_received_node = f"station_{station_id}_params_received"
-    start_node          = f"station_{station_id}_start"
-    complete_node       = f"station_{station_id}_process_complete"
-
-    # ① PC 复位三个状态位（避免上一轮影响）
-    self._reset_station_process_flags(station_id)
-
-    # ② 等 PLC 主动请求参数（PLC 准备好了才接收）
-    while not self.get_node_value(request_node):
-        time.sleep(1.0)
-
-    # ③ PC 下发参数（注意：PLC 内部数组是 0-based，PC 暴露给用户是 1-based）
-    station_idx = station_id - 1
-    self.set_node_value(f"mag_stirrer_c{station_idx}_stir_speed", mag_stir_speed)
-    self.set_node_value(f"mag_stirrer_c{station_idx}_heat_temp",  mag_stir_heat_temp)
-    self.set_node_value(f"mag_stirrer_c{station_idx}_time_set",   mag_stir_time_set)
-    self.set_node_value(f"syringe_pump_{station_idx}_abs_position_set", syringe_pump_abs_pos)
-
-    # ④ PC 通知 PLC "参数已就绪"，等 PLC 回复"已执行"
-    self.set_node_value(start_node, True)
-    while not self.get_node_value(params_received_node):
-        time.sleep(1.0)
-
-    # ⑤ 等 PLC 完成整个工艺
-    while not self.get_node_value(complete_node):
-        time.sleep(5.0)
-
-    self.set_node_value(start_node, False)   # 复位，方便下一轮
-    return {"station_id": station_id, "message": "..."}
-```
-
-四个状态位的语义：
-
-| 信号 | 方向 | 含义 |
-|---|---|---|
-| `station_X_request_params` | **PLC → PC** | "我准备好了，把参数给我" |
-| `station_X_start` | **PC → PLC** | "参数我已经写好了，开干" |
-| `station_X_params_received` | **PLC → PC** | "参数我已经吃下了" |
-| `station_X_process_complete` | **PLC → PC** | "工艺已经做完" |
-
-**这是 PLC 通信教科书级别的标准范式**，所有带数据下发的动作都建议照抄。
-
-#### 范式 C：编号下发 + 编号对应的完成信号（多目标互锁）
-
-```python
-def trigger_robot_pick_beaker(self, pick_beaker_id: int, place_station_id: int = None, ...):
-    # ① 等机器人空闲（互锁）
-    while not self.get_node_value("robot_ready"):
-        time.sleep(1.0)
-
-    # ② 阶段一：下发"取哪一杯"编号 + 等"取这一杯完成"
-    pick_complete_node  = f"robot_rack_pick_beaker_{pick_beaker_id}_complete"
-    self.set_node_value("robot_pick_beaker_id", pick_beaker_id)
-    while not self.get_node_value(pick_complete_node):
-        time.sleep(1.0)
-
-    # ③ 阶段二：下发"放到哪个工站"编号 + 等"放完成"
-    place_complete_node = f"robot_place_station_{place_station_id}_complete"
-    self._reset_station_process_flags(place_station_id)
-    self.set_node_value("robot_place_station_id", place_station_id)
-    while not self.get_node_value(place_complete_node):
-        time.sleep(1.0)
-```
-
-要点：
- **同一个动作的多个目标用"编号变量 + 编号对应的完成信号"实现**，不要每个目标都开一个开始位。
- **配合 Python 端 `threading.Lock()` 做软互锁**，避免多个线程争抢机器人。
- **每个阶段有独立的完成信号**，串行等待，不能合并。
-
-### 4.3 一些容易踩坑的细节
-
-1. **节点名映射**
-   `set_node_value("alarm_reset", True)` 实际写入的是 CSV 中文名 `报警复位`，
-   `get_node_value` 同理。**业务代码全部用 EnglishName**，不要直接用中文。
-
-2. **PLC 数组索引和 PC 不一致**
-   AI4M 里 PC 暴露 `station_id ∈ {1, 2, 3}`，但 PLC 内部数组是 `C[0..2]`，
-   驱动里要做 `station_idx = station_id - 1`，**这种映射只在驱动层做一次**，
-   不要让上层（registry / 实验记录本）感知。
-
-3. **订阅模式下 BOOL 节点的边沿同步**
-   订阅有 ~500ms 延迟。如果你刚 `set_node_value(x, True)` 就立刻 `get_node_value(x)`，
-   读到的可能还是 `False`（订阅还没推回来）。
-   解决方案：**写完后用 `force_read=True` 透传一次** 或加一段 `time.sleep`。
-
-4. **永远不要忘记复位**
-   `start` 拉 True 后必须有地方拉回 False，否则下一轮 PLC 上升沿不触发。
-   AI4M 在 `_reset_station_process_flags` 中统一做：
-
-   ```python
-   def _reset_station_process_flags(self, station_id: int) -> None:
-       self.set_node_value(f"station_{station_id}_process_complete", False)
-       self.set_node_value(f"station_{station_id}_start", False)
-       self.set_node_value(f"station_{station_id}_params_received", False)
-   ```
-
-5. **耗时长的等待 sleep 加大**
-   工艺等待用 `time.sleep(5.0)`，机器人等待用 `time.sleep(1.0)`，初始化等待 `time.sleep(1.0)`，
-   不要全部用 0.1s 轮询，会把日志刷爆。
-
---
-
-## 5. 把驱动接到 Uni-Lab：Registry + Graph
-
-### 5.1 Registry YAML（动作 schema）
-
-文件：`unilabos/registry/devices/AI4M_station.yaml`
-
-```yaml
-AI4M_station:
-  category: [AI4M_station]
-  class:
-    module: unilabos.devices.workstation.AI4M.AI4M:AI4MDevice    # ← 入口类
-    type: python
-    action_value_mappings:
-      auto-trigger_init:
-        schema:
-          description: 设备初始化...
-          properties:
-            goal:    { properties: {}, required: [], type: object }
-            result:
-              properties: { message: { type: string } }
-              required: [message]
-              type: object
-          type: object
-        type: UniLabJsonCommand
-
-      auto-trigger_station_process:
-        always_free: true
-        schema:
-          description: 执行检测工艺流程
-          properties:
-            goal:
-              properties:
-                station_id:                   { type: integer, description: 检测编号 1-3 }
-                mag_stir_stir_speed:          { type: integer }
-                mag_stir_heat_temp:           { type: integer }
-                mag_stir_time_set:            { type: integer }
-                syringe_pump_abs_position_set:{ type: integer }
-              required: [station_id, mag_stir_stir_speed, mag_stir_heat_temp,
-                         mag_stir_time_set, syringe_pump_abs_position_set]
-              type: object
-            result: { ... }
-        type: UniLabJsonCommand
-
-  init_param_schema:
-    config:
-      type: object
-      required: [url]
-      properties:
-        url:                   { type: string,  description: OPC UA 服务器地址 }
-        csv_path:              { type: string,  description: 节点配置 CSV 路径 }
-        deck:                  { type: string,  description: 资源树配置 }
-        username:              { type: string }
-        password:              { type: string }
-        use_subscription:      { type: boolean, default: true }
-        cache_timeout:         { type: number,  default: 5.0 }
-        subscription_interval: { type: integer, default: 500 }
-```
-
-规则总结：
- `class.module` 指向驱动类（`module:ClassName`）。
- `action_value_mappings` 中的 key 形如 `auto-<方法名>`，对应驱动里的同名 Python 方法。
- `schema.goal` 自动转成 ROS2 Action 的 goal 消息，`schema.result` 转 result。
- `init_param_schema.config` 对应 `__init__` 的入参，**所有需要现场改的参数都要列出来**（最重要的就是 `url` 和 `csv_path`）。
- `always_free: true` 表示该动作不占用工站独占锁（多检测站可并发执行）。
-
-### 5.2 Graph JSON（实例化）
-
-文件：`unilabos/devices/workstation/AI4M/AI4M.json`
-
-```json
-{
-  "nodes": [
-    {
-      "id": "AI4M_station",
-      "name": "AI4M_station",
-      "type": "device",
-      "class": "AI4M_station",
-      "children": ["AI4M_deck"],
-      "parent": null,
-      "config": {
-        "url": "opc.tcp://192.168.1.10:4840",
-        "csv_path": "opcua_nodes_AI4M.csv",
-        "deck": {
-          "data": {
-            "_resource_child_name": "AI4M_deck",
-            "_resource_type": "unilabos.devices.workstation.AI4M.decks:AI4M_deck"
-          }
-        }
-      }
-    },
-    {
-      "id": "AI4M_deck",
-      "type": "deck",
-      "class": "AI4M_deck",
-      "parent": "AI4M_station",
-      "config": { "type": "AI4M_deck" }
-    }
-  ]
-}
-```
-
-要点：
- `class` 必须和 Registry YAML 的顶层 key 完全一致（`AI4M_station`）。
- `config` 字段**逐字传给驱动 `__init__`**，所以 Graph JSON = "现场参数表"。
- 多套相同设备时拷贝一份，把 `id` / `url` 改掉即可（参考 `AI4M002_station`）。
-
-### 5.3 启动命令（来自 `start.md`）
-
-```cmd
-# 真机
-python unilabos/app/main.py -g unilabos/devices/workstation/AI4M/AI4M.json `
-  --ak <ak> --sk <sk> --upload_registry --addr <api_url> --disable_browser
-
-# 仿真（KEPServerEX 跑在本机 49320 端口）
-python unilabos/app/main.py -g unilabos/devices/workstation/AI4M/AI4Msim.json `
-  --ak <ak> --sk <sk> --upload_registry --disable_browser
-```
-
-`--upload_registry` 会把 `AI4M_station.yaml` 的 schema 上传到云端，
-之后实验记录本就能看到所有 `auto-*` 动作。
-
---
-
-## 6. 调试方法
-
-### 6.1 用 KEPServerEX 仿真 PLC
-
-不带 PLC 的开发机上，可以用 KEPServerEX（或 `python-opcua` 自建 server）模拟。
-AI4M 提供了一份仿真节点表 `opcua_nodes_AI4M_sim.csv`，**只改 NodeId 不改语义**，
-所以驱动代码无需任何改动即可在本机调试。
-
-### 6.2 单独跑驱动（不开 ROS）
-
-在驱动文件末尾的 `if __name__ == '__main__':` 段：
-
-```python
-if __name__ == '__main__':
-    A4 = AI4MDevice(
-        url="opc.tcp://192.168.1.10:4840",
-        csv_path="opcua_nodes_AI4M.csv",
-    )
-    A4.trigger_init()
-    print("初始化完成")
-    A4.trigger_robot_pick_beaker(1, 1)
-```
-
-**新动作上线前一定要在这里裸跑一遍**，确认握手时序正确，再往上接 ROS。
-
-### 6.3 看日志判断卡在哪
-
-`base_opcua_client.py` 的日志已经覆盖了所有关键节点：
-
-```
-✓ 客户端已连接!
-✓ 找到变量节点: 'robot_ready', NodeId: ns=4;s=...
-✓ 已订阅节点: robot_ready
-✓ 节点查找完成：所有 142 个节点均已找到
-```
-
-如果看到 `⚠ 以下 N 个节点未找到`，**99% 是 CSV 里的 NodeId 写错了**，回去对一下 PLC 工程导出的 NodeId。
-
-### 6.4 检查节点是否能直接读写
-
-```python
-# 透传读，绕过订阅缓存
-A4.get_node_value("robot_ready", force_read=True)
-
-# 直接读 JSON 形式（适合从 HTTP/调试面板调）
-A4.read_node("robot_ready")
-
-# 写
-A4.set_node_value("alarm_reset", True)
-A4.write_node('{"node_name": "alarm_reset", "value": false}')
-```
-
---
-
-## 7. 接入新 PLC 设备的 Checklist
-
-接到一台新工站时，按下面顺序做就能保证不漏：
-
- [ ] 1. 让 PLC 工程师把上位通讯变量整理到 OPC UA Server，导出 NodeId 清单。
- [ ] 2. 在 `unilabos/devices/workstation/<设备名>/` 下新建目录，复制 `AI4M/base_opcua_client.py` 不动。
- [ ] 3. 整理 `opcua_nodes_<设备名>.csv`，6 列填齐，并补上 `EnglishName`。
- [ ] 4. 在该目录写设备驱动 `<设备名>.py`，继承 `OpcUaClientWithSubscription`：
-  - [ ] `__init__` 调用 `super().__init__` + `self.load_nodes_from_csv(csv_path)`。
-  - [ ] 每个动作函数用范式 A/B/C 写握手协议。
-  - [ ] 每个动作函数都返回 `dict`，至少含 `message` 字段。
- [ ] 5. 在 `unilabos/registry/devices/` 下新建 `<设备名>_station.yaml`，配置 `init_param_schema` 和 `action_value_mappings`。
- [ ] 6. 在该目录新建 `<设备名>.json`（Graph），填好 `url` 和 `csv_path`。
- [ ] 7. 用 `if __name__ == '__main__':` 单独跑驱动确认握手 OK。
- [ ] 8. 用 `python unilabos/app/main.py -g <Graph> --upload_registry ...` 上线，到实验记录本下发动作回归。
-
---
-
-## 8. 参考实现速查
-
-| 关注点 | 在 AI4M 中看哪里 |
-|---|---|
-| OPC UA 通信基类 | `base_opcua_client.py` |
-| 节点定义类型系统 | `unilabos/device_comms/opcua_client/node/uniopcua.py` |
-| 节点表 CSV 标准 | `opcua_nodes_AI4M.csv` |
-| 设备驱动入口类 | `AI4M.py: AI4MDevice` |
-| 握手范式 A（脉冲+完成） | `AI4M.py: trigger_init` |
-| 握手范式 B（请求/参数/完成） | `AI4M.py: trigger_station_process` |
-| 握手范式 C（编号+完成） | `AI4M.py: trigger_robot_pick_beaker` |
-| 自动模式批量参数下发 | `AI4M.py: download_auto_params` |
-| Registry schema | `unilabos/registry/devices/AI4M_station.yaml` |
-| Graph 实例化 | `AI4M.json` / `AI4Msim.json` |
-| 启动命令 | `start.md` |
--- a/recipes/msgs/recipe.yaml
+++ b/recipes/msgs/recipe.yaml
@@ -1,6 +1,6 @@
 package:
  name: ros-humble-unilabos-msgs
-  version: 0.11.3
+  version: 0.11.2
 source:
  path: ../../unilabos_msgs
  target_directory: src
--- a/recipes/unilabos/recipe.yaml
+++ b/recipes/unilabos/recipe.yaml
@@ -1,6 +1,6 @@
 package:
  name: unilabos
-  version: "0.11.3"
+  version: "0.11.2"

 source:
  path: ../..
--- a/scripts/workflow.py
+++ b/scripts/workflow.py
@@ -2,6 +2,7 @@ import json
 import logging
 import traceback
 import uuid
+import xml.etree.ElementTree as ET
 from typing import Any, Dict, List

 import networkx as nx
@@ -24,15 +25,7 @@ class SimpleGraph:

    def add_edge(self, source, target, **attrs):
        """添加边"""
-        # edge = {"source": source, "target": target, **attrs}
-        edge = {
-            "source": source, "target": target,
-            "source_node_uuid": source,
-            "target_node_uuid": target,
-            "source_handle_io": "source",
-            "target_handle_io": "target",
-            **attrs
-        }
+        edge = {"source": source, "target": target, **attrs}
        self.edges.append(edge)

    def to_dict(self):
@@ -49,7 +42,6 @@ class SimpleGraph:
            "multigraph": False,
            "graph": {},
            "nodes": nodes_list,
-            "edges": self.edges,
            "links": self.edges,
        }

@@ -66,8 +58,495 @@ def extract_json_from_markdown(text: str) -> str:
    return text


+def convert_to_type(val: str) -> Any:
+    """将字符串值转换为适当的数据类型"""
+    if val == "True":
+        return True
+    if val == "False":
+        return False
+    if val == "?":
+        return None
+    if val.endswith(" g"):
+        return float(val.split(" ")[0])
+    if val.endswith("mg"):
+        return float(val.split("mg")[0])
+    elif val.endswith("mmol"):
+        return float(val.split("mmol")[0]) / 1000
+    elif val.endswith("mol"):
+        return float(val.split("mol")[0])
+    elif val.endswith("ml"):
+        return float(val.split("ml")[0])
+    elif val.endswith("RPM"):
+        return float(val.split("RPM")[0])
+    elif val.endswith(" °C"):
+        return float(val.split(" ")[0])
+    elif val.endswith(" %"):
+        return float(val.split(" ")[0])
+    return val


+def refactor_data(data: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
+    """统一的数据重构函数，根据操作类型自动选择模板"""
+    refactored_data = []
+
+    # 定义操作映射，包含生物实验和有机化学的所有操作
+    OPERATION_MAPPING = {
+        # 生物实验操作
+        "transfer_liquid": "SynBioFactory-liquid_handler.prcxi-transfer_liquid",
+        "transfer": "SynBioFactory-liquid_handler.biomek-transfer",
+        "incubation": "SynBioFactory-liquid_handler.biomek-incubation",
+        "move_labware": "SynBioFactory-liquid_handler.biomek-move_labware",
+        "oscillation": "SynBioFactory-liquid_handler.biomek-oscillation",
+        # 有机化学操作
+        "HeatChillToTemp": "SynBioFactory-workstation-HeatChillProtocol",
+        "StopHeatChill": "SynBioFactory-workstation-HeatChillStopProtocol",
+        "StartHeatChill": "SynBioFactory-workstation-HeatChillStartProtocol",
+        "HeatChill": "SynBioFactory-workstation-HeatChillProtocol",
+        "Dissolve": "SynBioFactory-workstation-DissolveProtocol",
+        "Transfer": "SynBioFactory-workstation-TransferProtocol",
+        "Evaporate": "SynBioFactory-workstation-EvaporateProtocol",
+        "Recrystallize": "SynBioFactory-workstation-RecrystallizeProtocol",
+        "Filter": "SynBioFactory-workstation-FilterProtocol",
+        "Dry": "SynBioFactory-workstation-DryProtocol",
+        "Add": "SynBioFactory-workstation-AddProtocol",
+    }
+
+    UNSUPPORTED_OPERATIONS = ["Purge", "Wait", "Stir", "ResetHandling"]
+
+    for step in data:
+        operation = step.get("action")
+        if not operation or operation in UNSUPPORTED_OPERATIONS:
+            continue
+
+        # 处理重复操作
+        if operation == "Repeat":
+            times = step.get("times", step.get("parameters", {}).get("times", 1))
+            sub_steps = step.get("steps", step.get("parameters", {}).get("steps", []))
+            for i in range(int(times)):
+                sub_data = refactor_data(sub_steps)
+                refactored_data.extend(sub_data)
+            continue
+
+        # 获取模板名称
+        template = OPERATION_MAPPING.get(operation)
+        if not template:
+            # 自动推断模板类型
+            if operation.lower() in ["transfer", "incubation", "move_labware", "oscillation"]:
+                template = f"SynBioFactory-liquid_handler.biomek-{operation}"
+            else:
+                template = f"SynBioFactory-workstation-{operation}Protocol"
+
+        # 创建步骤数据
+        step_data = {
+            "template": template,
+            "description": step.get("description", step.get("purpose", f"{operation} operation")),
+            "lab_node_type": "Device",
+            "parameters": step.get("parameters", step.get("action_args", {})),
+        }
+        refactored_data.append(step_data)
+
+    return refactored_data
+
+
+def build_protocol_graph(
+    labware_info: List[Dict[str, Any]], protocol_steps: List[Dict[str, Any]], workstation_name: str
+) -> SimpleGraph:
+    """统一的协议图构建函数，根据设备类型自动选择构建逻辑"""
+    G = SimpleGraph()
+    resource_last_writer = {}
+    LAB_NAME = "SynBioFactory"
+
+    protocol_steps = refactor_data(protocol_steps)
+
+    # 检查协议步骤中的模板来判断协议类型
+    has_biomek_template = any(
+        ("biomek" in step.get("template", "")) or ("prcxi" in step.get("template", ""))
+        for step in protocol_steps
+    )
+
+    if has_biomek_template:
+        # 生物实验协议图构建
+        for labware_id, labware in labware_info.items():
+            node_id = str(uuid.uuid4())
+
+            labware_attrs = labware.copy()
+            labware_id = labware_attrs.pop("id", labware_attrs.get("name", f"labware_{uuid.uuid4()}"))
+            labware_attrs["description"] = labware_id
+            labware_attrs["lab_node_type"] = (
+                "Reagent" if "Plate" in str(labware_id) else "Labware" if "Rack" in str(labware_id) else "Sample"
+            )
+            labware_attrs["device_id"] = workstation_name
+
+            G.add_node(node_id, template=f"{LAB_NAME}-host_node-create_resource", **labware_attrs)
+            resource_last_writer[labware_id] = f"{node_id}:labware"
+
+        # 处理协议步骤
+        prev_node = None
+        for i, step in enumerate(protocol_steps):
+            node_id = str(uuid.uuid4())
+            G.add_node(node_id, **step)
+
+            # 添加控制流边
+            if prev_node is not None:
+                G.add_edge(prev_node, node_id, source_port="ready", target_port="ready")
+            prev_node = node_id
+
+            # 处理物料流
+            params = step.get("parameters", {})
+            if "sources" in params and params["sources"] in resource_last_writer:
+                source_node, source_port = resource_last_writer[params["sources"]].split(":")
+                G.add_edge(source_node, node_id, source_port=source_port, target_port="labware")
+
+            if "targets" in params:
+                resource_last_writer[params["targets"]] = f"{node_id}:labware"
+
+        # 添加协议结束节点
+        end_id = str(uuid.uuid4())
+        G.add_node(end_id, template=f"{LAB_NAME}-liquid_handler.biomek-run_protocol")
+        if prev_node is not None:
+            G.add_edge(prev_node, end_id, source_port="ready", target_port="ready")
+
+    else:
+        # 有机化学协议图构建
+        WORKSTATION_ID = workstation_name
+
+        # 为所有labware创建资源节点
+        for item_id, item in labware_info.items():
+            # item_id = item.get("id") or item.get("name", f"item_{uuid.uuid4()}")
+            node_id = str(uuid.uuid4())
+
+            # 判断节点类型
+            if item.get("type") == "hardware" or "reactor" in str(item_id).lower():
+                if "reactor" not in str(item_id).lower():
+                    continue
+                lab_node_type = "Sample"
+                description = f"Prepare Reactor: {item_id}"
+                liquid_type = []
+                liquid_volume = []
+            else:
+                lab_node_type = "Reagent"
+                description = f"Add Reagent to Flask: {item_id}"
+                liquid_type = [item_id]
+                liquid_volume = [1e5]
+
+            G.add_node(
+                node_id,
+                template=f"{LAB_NAME}-host_node-create_resource",
+                description=description,
+                lab_node_type=lab_node_type,
+                res_id=item_id,
+                device_id=WORKSTATION_ID,
+                class_name="container",
+                parent=WORKSTATION_ID,
+                bind_locations={"x": 0.0, "y": 0.0, "z": 0.0},
+                liquid_input_slot=[-1],
+                liquid_type=liquid_type,
+                liquid_volume=liquid_volume,
+                slot_on_deck="",
+                role=item.get("role", ""),
+            )
+            resource_last_writer[item_id] = f"{node_id}:labware"
+
+        last_control_node_id = None
+
+        # 处理协议步骤
+        for step in protocol_steps:
+            node_id = str(uuid.uuid4())
+            G.add_node(node_id, **step)
+
+            # 控制流
+            if last_control_node_id is not None:
+                G.add_edge(last_control_node_id, node_id, source_port="ready", target_port="ready")
+            last_control_node_id = node_id
+
+            # 物料流
+            params = step.get("parameters", {})
+            input_resources = {
+                "Vessel": params.get("vessel"),
+                "ToVessel": params.get("to_vessel"),
+                "FromVessel": params.get("from_vessel"),
+                "reagent": params.get("reagent"),
+                "solvent": params.get("solvent"),
+                "compound": params.get("compound"),
+                "sources": params.get("sources"),
+                "targets": params.get("targets"),
+            }
+
+            for target_port, resource_name in input_resources.items():
+                if resource_name and resource_name in resource_last_writer:
+                    source_node, source_port = resource_last_writer[resource_name].split(":")
+                    G.add_edge(source_node, node_id, source_port=source_port, target_port=target_port)
+
+            output_resources = {
+                "VesselOut": params.get("vessel"),
+                "FromVesselOut": params.get("from_vessel"),
+                "ToVesselOut": params.get("to_vessel"),
+                "FiltrateOut": params.get("filtrate_vessel"),
+                "reagent": params.get("reagent"),
+                "solvent": params.get("solvent"),
+                "compound": params.get("compound"),
+                "sources_out": params.get("sources"),
+                "targets_out": params.get("targets"),
+            }
+
+            for source_port, resource_name in output_resources.items():
+                if resource_name:
+                    resource_last_writer[resource_name] = f"{node_id}:{source_port}"
+
+    return G
+
+
+def draw_protocol_graph(protocol_graph: SimpleGraph, output_path: str):
+    """
+    (辅助功能) 使用 networkx 和 matplotlib 绘制协议工作流图，用于可视化。
+    """
+    if not protocol_graph:
+        print("Cannot draw graph: Graph object is empty.")
+        return
+
+    G = nx.DiGraph()
+
+    for node_id, attrs in protocol_graph.nodes.items():
+        label = attrs.get("description", attrs.get("template", node_id[:8]))
+        G.add_node(node_id, label=label, **attrs)
+
+    for edge in protocol_graph.edges:
+        G.add_edge(edge["source"], edge["target"])
+
+    plt.figure(figsize=(20, 15))
+    try:
+        pos = nx.nx_agraph.graphviz_layout(G, prog="dot")
+    except Exception:
+        pos = nx.shell_layout(G)  # Fallback layout
+
+    node_labels = {node: data["label"] for node, data in G.nodes(data=True)}
+    nx.draw(
+        G,
+        pos,
+        with_labels=False,
+        node_size=2500,
+        node_color="skyblue",
+        node_shape="o",
+        edge_color="gray",
+        width=1.5,
+        arrowsize=15,
+    )
+    nx.draw_networkx_labels(G, pos, labels=node_labels, font_size=8, font_weight="bold")
+
+    plt.title("Chemical Protocol Workflow Graph", size=15)
+    plt.savefig(output_path, dpi=300, bbox_inches="tight")
+    plt.close()
+    print(f"  - Visualization saved to '{output_path}'")
+
+
+from networkx.drawing.nx_agraph import to_agraph
+import re
+
+COMPASS = {"n","e","s","w","ne","nw","se","sw","c"}
+
+def _is_compass(port: str) -> bool:
+    return isinstance(port, str) and port.lower() in COMPASS
+
+def draw_protocol_graph_with_ports(protocol_graph, output_path: str, rankdir: str = "LR"):
+    """
+    使用 Graphviz 端口语法绘制协议工作流图。
+    - 若边上的 source_port/target_port 是 compass（n/e/s/w/...），直接用 compass。
+    - 否则自动为节点创建 record 形状并定义命名端口 <portname>。
+    最终由 PyGraphviz 渲染并输出到 output_path（后缀决定格式，如 .png/.svg/.pdf）。
+    """
+    if not protocol_graph:
+        print("Cannot draw graph: Graph object is empty.")
+        return
+
+    # 1) 先用 networkx 搭建有向图，保留端口属性
+    G = nx.DiGraph()
+    for node_id, attrs in protocol_graph.nodes.items():
+        label = attrs.get("description", attrs.get("template", node_id[:8]))
+        # 保留一个干净的“中心标签”，用于放在 record 的中间槽
+        G.add_node(node_id, _core_label=str(label), **{k:v for k,v in attrs.items() if k not in ("label",)})
+
+    edges_data = []
+    in_ports_by_node  = {}  # 收集命名输入端口
+    out_ports_by_node = {}  # 收集命名输出端口
+
+    for edge in protocol_graph.edges:
+        u = edge["source"]
+        v = edge["target"]
+        sp = edge.get("source_port")
+        tp = edge.get("target_port")
+
+        # 记录到图里（保留原始端口信息）
+        G.add_edge(u, v, source_port=sp, target_port=tp)
+        edges_data.append((u, v, sp, tp))
+
+        # 如果不是 compass，就按“命名端口”先归类，等会儿给节点造 record
+        if sp and not _is_compass(sp):
+            out_ports_by_node.setdefault(u, set()).add(str(sp))
+        if tp and not _is_compass(tp):
+            in_ports_by_node.setdefault(v, set()).add(str(tp))
+
+    # 2) 转为 AGraph，使用 Graphviz 渲染
+    A = to_agraph(G)
+    A.graph_attr.update(rankdir=rankdir, splines="true", concentrate="false", fontsize="10")
+    A.node_attr.update(shape="box", style="rounded,filled", fillcolor="lightyellow", color="#999999", fontname="Helvetica")
+    A.edge_attr.update(arrowsize="0.8", color="#666666")
+
+    # 3) 为需要命名端口的节点设置 record 形状与 label
+    #    左列 = 输入端口；中间 = 核心标签；右列 = 输出端口
+    for n in A.nodes():
+        node = A.get_node(n)
+        core = G.nodes[n].get("_core_label", n)
+
+        in_ports  = sorted(in_ports_by_node.get(n, []))
+        out_ports = sorted(out_ports_by_node.get(n, []))
+
+        # 如果该节点涉及命名端口，则用 record；否则保留原 box
+        if in_ports or out_ports:
+            def port_fields(ports):
+                if not ports:
+                    return " "  # 必须留一个空槽占位
+                # 每个端口一个小格子，<p> name
+                return "|".join(f"<{re.sub(r'[^A-Za-z0-9_:.|-]', '_', p)}> {p}" for p in ports)
+
+            left  = port_fields(in_ports)
+            right = port_fields(out_ports)
+
+            # 三栏：左(入) | 中(节点名) | 右(出)
+            record_label = f"{{ {left} | {core} | {right} }}"
+            node.attr.update(shape="record", label=record_label)
+        else:
+            # 没有命名端口：普通盒子，显示核心标签
+            node.attr.update(label=str(core))
+
+    # 4) 给边设置 headport / tailport
+    #    - 若端口为 compass：直接用 compass（e.g., headport="e"）
+    #    - 若端口为命名端口：使用在 record 中定义的 <port> 名（同名即可）
+    for (u, v, sp, tp) in edges_data:
+        e = A.get_edge(u, v)
+
+        # Graphviz 属性：tail 是源，head 是目标
+        if sp:
+            if _is_compass(sp):
+                e.attr["tailport"] = sp.lower()
+            else:
+                # 与 record label 中 <port> 名一致；特殊字符已在 label 中做了清洗
+                e.attr["tailport"] = re.sub(r'[^A-Za-z0-9_:.|-]', '_', str(sp))
+
+        if tp:
+            if _is_compass(tp):
+                e.attr["headport"] = tp.lower()
+            else:
+                e.attr["headport"] = re.sub(r'[^A-Za-z0-9_:.|-]', '_', str(tp))
+
+        # 可选：若想让边更贴边缘，可设置 constraint/spline 等
+        # e.attr["arrowhead"] = "vee"
+
+    # 5) 输出
+    A.draw(output_path, prog="dot")
+    print(f"  - Port-aware workflow rendered to '{output_path}'")
+
+
+def flatten_xdl_procedure(procedure_elem: ET.Element) -> List[ET.Element]:
+    """展平嵌套的XDL程序结构"""
+    flattened_operations = []
+    TEMP_UNSUPPORTED_PROTOCOL = ["Purge", "Wait", "Stir", "ResetHandling"]
+
+    def extract_operations(element: ET.Element):
+        if element.tag not in ["Prep", "Reaction", "Workup", "Purification", "Procedure"]:
+            if element.tag not in TEMP_UNSUPPORTED_PROTOCOL:
+                flattened_operations.append(element)
+
+        for child in element:
+            extract_operations(child)
+
+    for child in procedure_elem:
+        extract_operations(child)
+
+    return flattened_operations
+
+
+def parse_xdl_content(xdl_content: str) -> tuple:
+    """解析XDL内容"""
+    try:
+        xdl_content_cleaned = "".join(c for c in xdl_content if c.isprintable())
+        root = ET.fromstring(xdl_content_cleaned)
+
+        synthesis_elem = root.find("Synthesis")
+        if synthesis_elem is None:
+            return None, None, None
+
+        # 解析硬件组件
+        hardware_elem = synthesis_elem.find("Hardware")
+        hardware = []
+        if hardware_elem is not None:
+            hardware = [{"id": c.get("id"), "type": c.get("type")} for c in hardware_elem.findall("Component")]
+
+        # 解析试剂
+        reagents_elem = synthesis_elem.find("Reagents")
+        reagents = []
+        if reagents_elem is not None:
+            reagents = [{"name": r.get("name"), "role": r.get("role", "")} for r in reagents_elem.findall("Reagent")]
+
+        # 解析程序
+        procedure_elem = synthesis_elem.find("Procedure")
+        if procedure_elem is None:
+            return None, None, None
+
+        flattened_operations = flatten_xdl_procedure(procedure_elem)
+        return hardware, reagents, flattened_operations
+
+    except ET.ParseError as e:
+        raise ValueError(f"Invalid XDL format: {e}")
+
+
+def convert_xdl_to_dict(xdl_content: str) -> Dict[str, Any]:
+    """
+    将XDL XML格式转换为标准的字典格式
+
+    Args:
+        xdl_content: XDL XML内容
+
+    Returns:
+        转换结果，包含步骤和器材信息
+    """
+    try:
+        hardware, reagents, flattened_operations = parse_xdl_content(xdl_content)
+        if hardware is None:
+            return {"error": "Failed to parse XDL content", "success": False}
+
+        # 将XDL元素转换为字典格式
+        steps_data = []
+        for elem in flattened_operations:
+            # 转换参数类型
+            parameters = {}
+            for key, val in elem.attrib.items():
+                converted_val = convert_to_type(val)
+                if converted_val is not None:
+                    parameters[key] = converted_val
+
+            step_dict = {
+                "operation": elem.tag,
+                "parameters": parameters,
+                "description": elem.get("purpose", f"Operation: {elem.tag}"),
+            }
+            steps_data.append(step_dict)
+
+        # 合并硬件和试剂为统一的labware_info格式
+        labware_data = []
+        labware_data.extend({"id": hw["id"], "type": "hardware", **hw} for hw in hardware)
+        labware_data.extend({"name": reagent["name"], "type": "reagent", **reagent} for reagent in reagents)
+
+        return {
+            "success": True,
+            "steps": steps_data,
+            "labware": labware_data,
+            "message": f"Successfully converted XDL to dict format. Found {len(steps_data)} steps and {len(labware_data)} labware items.",
+        }
+
+    except Exception as e:
+        error_msg = f"XDL conversion failed: {str(e)}"
+        logger.error(error_msg)
+        return {"error": error_msg, "success": False}


 def create_workflow(
--- a/setup.py
+++ b/setup.py
@@ -4,7 +4,7 @@ package_name = 'unilabos'

 setup(
    name=package_name,
-    version='0.11.3',
+    version='0.11.2',
    packages=find_packages(),
    include_package_data=True,
    install_requires=['setuptools'],
--- a/unilabos/init.py
+++ b/unilabos/init.py
@@ -1 +1 @@
-__version__ = "0.11.3"
+__version__ = "0.11.2"
--- a/unilabos/app/model.py
+++ b/unilabos/app/model.py
@@ -59,7 +59,6 @@ class JobAddReq(BaseModel):
    task_id: str = Field(examples=["task_id"], description="task uuid (auto-generated if empty)", default="")
    job_id: str = Field(examples=["job_id"], description="goal uuid (auto-generated if empty)", default="")
    node_id: str = Field(examples=["node_id"], description="node uuid", default="")
-    notebook_id: str = Field(examples=["notebook_id"], description="notebook uuid", default="")
    server_info: dict = Field(
        examples=[{"send_timestamp": 1717000000.0}],
        description="server info (auto-generated if empty)",
--- a/unilabos/app/web/controller.py
+++ b/unilabos/app/web/controller.py
@@ -320,7 +320,6 @@ def job_add(req: JobAddReq) -> JobData:
            action_name=action_name,
            task_id=task_id,
            job_id=job_id,
-            notebook_id=req.notebook_id,
            device_action_key=device_action_key,
        )

--- a/unilabos/app/ws_client.py
+++ b/unilabos/app/ws_client.py
@@ -59,7 +59,6 @@ class QueueItem:
    action_name: str
    task_id: str
    job_id: str
-    notebook_id: str
    device_action_key: str
    next_run_time: float = 0  # 下次执行时间戳
    retry_count: int = 0  # 重试次数
@@ -72,7 +71,6 @@ class JobInfo:
    job_id: str
    task_id: str
    device_id: str
-    notebook_id: str
    action_name: str
    device_action_key: str
    status: JobStatus
@@ -541,10 +539,7 @@ class MessageProcessor:
                self.reconnect_count += 1
                backoff = WSConfig.reconnect_interval
                logger.info(
-                    "[MessageProcessor] 即将在 %s 秒后重连 (已尝试 %s/%s)",
-                    backoff,
-                    self.reconnect_count,
-                    WSConfig.max_reconnect_attempts,
+                    f"[MessageProcessor] 即将在 {backoff} 秒后重连 (已尝试 {self.reconnect_count}/{WSConfig.max_reconnect_attempts})"
                )
                await asyncio.sleep(backoff)
            else:
@@ -708,7 +703,6 @@ class MessageProcessor:
        action_name = data.get("action_name", "")
        task_id = data.get("task_id", "")
        job_id = data.get("job_id", "")
-        notebook_id = data.get("notebook_id", "")

        if not all([device_id, action_name, task_id, job_id]):
            logger.error("[MessageProcessor] Missing required fields in query_action_state")
@@ -724,7 +718,6 @@ class MessageProcessor:
            job_id=job_id,
            task_id=task_id,
            device_id=device_id,
-            notebook_id=notebook_id,
            action_name=action_name,
            device_action_key=device_action_key,
            status=JobStatus.QUEUE,
@@ -739,27 +732,13 @@ class MessageProcessor:
        if can_start_immediately:
            # 可以立即开始
            await self._send_action_state_response(
-                device_id,
-                action_name,
-                task_id,
-                job_id,
-                "query_action_status",
-                True,
-                0,
-                notebook_id=notebook_id,
+                device_id, action_name, task_id, job_id, "query_action_status", True, 0
            )
            logger.trace(f"[MessageProcessor] Job {job_log} can start immediately")
        else:
            # 需要排队
            await self._send_action_state_response(
-                device_id,
-                action_name,
-                task_id,
-                job_id,
-                "query_action_status",
-                False,
-                10,
-                notebook_id=notebook_id,
+                device_id, action_name, task_id, job_id, "query_action_status", False, 10
            )
            logger.trace(f"[MessageProcessor] Job {job_log} queued")

@@ -789,7 +768,6 @@ class MessageProcessor:
                        job_id=req.job_id,
                        task_id=req.task_id,
                        device_id=req.device_id,
-                        notebook_id=req.notebook_id,
                        action_name=action_name,
                        device_action_key=device_action_key,
                        status=JobStatus.QUEUE,
@@ -797,16 +775,11 @@ class MessageProcessor:
                        always_free=True,
                    )
                    self.device_manager.add_queue_request(job_info)
-                    existing_job = job_info
                    logger.info(f"[MessageProcessor] Job {job_log} always_free, auto-registered from direct job_start")
                else:
                    logger.error(f"[MessageProcessor] Job {job_log} not registered (missing query_action_state)")
                    return

-            if existing_job and req.notebook_id and not existing_job.notebook_id:
-                existing_job.notebook_id = req.notebook_id
-            notebook_id = req.notebook_id or (existing_job.notebook_id if existing_job else "")
-
            success = self.device_manager.start_job(req.job_id)
            if not success:
                logger.error(f"[MessageProcessor] Failed to start job {job_log}")
@@ -822,7 +795,6 @@ class MessageProcessor:
                action_name=req.action,
                task_id=req.task_id,
                job_id=req.job_id,
-                notebook_id=notebook_id,
                device_action_key=device_action_key,
            )

@@ -862,7 +834,6 @@ class MessageProcessor:
                            "job_id": req.job_id,
                            "task_id": req.task_id,
                            "device_id": req.device_id,
-                            "notebook_id": queue_item.notebook_id,
                            "action_name": req.action,
                            "status": "failed",
                            "feedback_data": {},
@@ -884,7 +855,6 @@ class MessageProcessor:
                            "query_action_status",
                            True,
                            0,
-                            notebook_id=next_job.notebook_id,
                        )
                        next_job_log = format_job_log(
                            next_job.job_id, next_job.task_id, next_job.device_id, next_job.action_name
@@ -1034,16 +1004,11 @@ class MessageProcessor:

                    success = host_node.notify_resource_tree_update(dev_id, act, item_list)

-                    if success is True:
+                    if success:
                        logger.info(
                            f"[MessageProcessor] Resource tree {act} completed for device {dev_id}, "
                            f"items: {len(item_list)}"
                        )
-                    elif success is None:
-                        logger.info(
-                            f"[MessageProcessor] Resource tree {act} skipped for device {dev_id}: "
-                            "在线增加设备暂不支持"
-                        )
                    else:
                        logger.warning(f"[MessageProcessor] Resource tree {act} failed for device {dev_id}")

@@ -1067,11 +1032,6 @@ class MessageProcessor:

        for item in device_list:
            target_node_id = item.get("target_node_id", "host_node")
-            if action == "add":
-                logger.info(
-                    f"[DeviceManage] 在线增加设备暂不支持，跳过 add_device: {item.get('id', '')}"
-                )
-                continue

            def _notify(target_id: str, act: str, cfg: ResourceDictType):
                try:
@@ -1141,15 +1101,7 @@ class MessageProcessor:
        logger.info(f"[MessageProcessor] Restart cleanup scheduled")

    async def _send_action_state_response(
-        self,
-        device_id: str,
-        action_name: str,
-        task_id: str,
-        job_id: str,
-        typ: str,
-        free: bool,
-        need_more: int,
-        notebook_id: str = "",
+        self, device_id: str, action_name: str, task_id: str, job_id: str, typ: str, free: bool, need_more: int
    ):
        """发送动作状态响应"""
        message = {
@@ -1160,7 +1112,6 @@ class MessageProcessor:
                "action_name": action_name,
                "task_id": task_id,
                "job_id": job_id,
-                "notebook_id": notebook_id,
                "free": free,
                "need_more": need_more + 1,
            },
@@ -1243,7 +1194,6 @@ class QueueProcessor:
                            action_name=timeout_job.action_name,
                            task_id=timeout_job.task_id,
                            job_id=timeout_job.job_id,
-                            notebook_id=timeout_job.notebook_id,
                            device_action_key=timeout_job.device_action_key,
                        )
                        # 发布超时失败状态，这会触发正常的job完成流程
@@ -1302,7 +1252,6 @@ class QueueProcessor:
                    "action_name": job_info.action_name,
                    "task_id": job_info.task_id,
                    "job_id": job_info.job_id,
-                    "notebook_id": job_info.notebook_id,
                    "free": False,
                    "need_more": 10 + 1,
                },
@@ -1342,7 +1291,6 @@ class QueueProcessor:
                    "action_name": job_info.action_name,
                    "task_id": job_info.task_id,
                    "job_id": job_info.job_id,
-                    "notebook_id": job_info.notebook_id,
                    "free": False,
                    "need_more": 10 + 1,
                },
@@ -1388,15 +1336,12 @@ class QueueProcessor:
                    "action_name": next_job.action_name,
                    "task_id": next_job.task_id,
                    "job_id": next_job.job_id,
-                    "notebook_id": next_job.notebook_id,
                    "free": True,
                    "need_more": 0,
                },
            }
            self.message_processor.send_message(message)
-            # next_job_log = format_job_log(
-            #     next_job.job_id, next_job.task_id, next_job.device_id, next_job.action_name
-            # )
+            # next_job_log = format_job_log(next_job.job_id, next_job.task_id, next_job.device_id, next_job.action_name)
            # logger.debug(f"[QueueProcessor] Notified next job {next_job_log} can start")

            # 立即触发下一轮状态检查
@@ -1565,7 +1510,6 @@ class WebSocketClient(BaseCommunicationClient):
                "job_id": item.job_id,
                "task_id": item.task_id,
                "device_id": item.device_id,
-                "notebook_id": item.notebook_id,
                "action_name": item.action_name,
                "status": status,
                "feedback_data": feedback_data,
--- a/unilabos/resources/graphio.py
+++ b/unilabos/resources/graphio.py
@@ -42,7 +42,7 @@ def canonicalize_nodes_data(
    Returns:
        ResourceTreeSet: 标准化后的资源树集合
    """
-    print_status(f"{len(nodes)} Resources loaded", "info")
+    print_status(f"{len(nodes)} Resources loaded:", "info")

    # 第一步：基本预处理（处理graphml的label字段）
    outer_host_node_id = None
--- a/unilabos/ros/nodes/base_device_node.py
+++ b/unilabos/ros/nodes/base_device_node.py
@@ -45,7 +45,6 @@ from unilabos.resources.graphio import (
 )
 from unilabos.resources.plr_additional_res_reg import register
 from unilabos.ros.msgs.message_converter import (
-    String,
    convert_to_ros_msg,
    convert_from_ros_msg_with_mapping,
    convert_to_ros_msg_with_mapping,
@@ -251,8 +250,7 @@ class PropertyPublisher:
    ):
        self.node = node
        self.name = name
-        self.msg_type = self._normalize_msg_type(msg_type)
-        self.original_msg_type = msg_type
+        self.msg_type = msg_type
        self.get_method = get_method
        self.timer_period = initial_period
        self.print_publish = print_publish
@@ -260,36 +258,16 @@ class PropertyPublisher:

        self._value = None
        try:
-            self.publisher_ = node.create_publisher(self.msg_type, f"{name}", qos)
+            self.publisher_ = node.create_publisher(msg_type, f"{name}", qos)
        except Exception as e:
            self.node.lab_logger().error(
-                f"StatusError, DeviceId: {self.node.device_id} 创建发布者 {name} 失败，"
-                f"可能由于注册表有误，类型: {msg_type}，错误: {e}"
+                f"StatusError, DeviceId: {self.node.device_id} 创建发布者 {name} 失败，可能由于注册表有误，类型: {msg_type}，错误: {e}"
            )
-            self.msg_type = String
-            try:
-                self.publisher_ = node.create_publisher(self.msg_type, f"{name}", qos)
-                self.node.lab_logger().warning(
-                    f"属性 {name} 的发布类型已降级为 String，原始类型: {msg_type}"
-                )
-            except Exception:
-                self.publisher_ = None
        self.timer = node.create_timer(self.timer_period, self.publish_property)
        self.__loop = ROS2DeviceNode.get_asyncio_loop()
-        str_msg_type = str(self.msg_type)[8:-2]
+        str_msg_type = str(msg_type)[8:-2]
        self.node.lab_logger().trace(f"发布属性: {name}, 类型: {str_msg_type}, 周期: {initial_period}秒, QoS: {qos}")

-    @staticmethod
-    def _normalize_msg_type(msg_type):
-        if msg_type in (dict, list, tuple, set) or msg_type in ("dict", "list", "tuple", "set"):
-            return String
-        return msg_type
-
-    def _normalize_value(self, value):
-        if self.msg_type is String and isinstance(value, (dict, list, tuple, set)):
-            return json.dumps(value, ensure_ascii=False, cls=TypeEncoder)
-        return value
-
    def get_property(self):
        if asyncio.iscoroutinefunction(self.get_method):
            # 如果是异步函数，运行事件循环并等待结果
@@ -324,16 +302,12 @@ class PropertyPublisher:
                pass
                # self.node.lab_logger().trace(f"【.publish_property】发布 {self.msg_type}: {value}")
            if value is not None:
-                if self.publisher_ is None:
-                    return
-                value = self._normalize_value(value)
                msg = convert_to_ros_msg(self.msg_type, value)
                self.publisher_.publish(msg)
                # self.node.lab_logger().trace(f"【.publish_property】属性 {self.name} 发布成功")
        except Exception as e:
-            topic = getattr(self.publisher_, "topic", self.name)
            self.node.lab_logger().error(
-                f"【.publish_property】发布属性 {topic} 出错: {str(e)}\n{traceback.format_exc()}"
+                f"【.publish_property】发布属性 {self.publisher_.topic} 出错: {str(e)}\n{traceback.format_exc()}"
            )

    def change_frequency(self, period):
--- a/unilabos/ros/nodes/presets/host_node.py
+++ b/unilabos/ros/nodes/presets/host_node.py
@@ -1691,9 +1691,7 @@ class HostNode(BaseROS2DeviceNode):
        else:
            self.lab_logger().warning("⚠️ 收到无效的Pong响应（缺少ping_id）")

-    def notify_resource_tree_update(
-        self, device_id: str, action: str, resource_uuid_list: List[str]
-    ) -> Optional[bool]:
+    def notify_resource_tree_update(self, device_id: str, action: str, resource_uuid_list: List[str]) -> bool:
        """
        通知设备节点更新资源树

@@ -1703,14 +1701,13 @@ class HostNode(BaseROS2DeviceNode):
            resource_uuid_list: 资源UUIDs

        Returns:
-            True if the update completed, False if it failed, None if it was intentionally skipped.
+            bool: 操作是否成功
        """
        try:
+            # 检查设备是否存在
            if device_id not in self.devices_names:
-                self.lab_logger().info(
-                    f"[Host Node-Resource] 在线增加设备暂不支持，跳过设备 {device_id} 的资源树 {action} 更新"
-                )
-                return None
+                self.lab_logger().error(f"[Host Node-Resource] Device {device_id} not found in devices_names")
+                return False

            namespace = self.devices_names[device_id]
            device_key = f"{namespace}/{device_id}"
--- a/unilabos/workflow/init.py
+++ b/unilabos/workflow/init.py
--- a/unilabos/workflow/from_python_script.py
+++ b/unilabos/workflow/from_python_script.py
@@ -1,241 +0,0 @@
-import ast
-import json
-from typing import Dict, List, Any, Tuple, Optional
-
-from .common import WorkflowGraph, RegistryAdapter
-
-Json = Dict[str, Any]
-
-# ---------------- Converter ----------------
-
-class DeviceMethodConverter:
-    """
-    - 字段统一：resource_name（原 device_class）、template_name（原 action_key）
-    - params 单层；inputs 使用 'params.' 前缀
-    - SimpleGraph.add_workflow_node 负责变量连线与边
-    """
-    def __init__(self, device_registry: Optional[Dict[str, Any]] = None):
-        self.graph = WorkflowGraph()
-        self.variable_sources: Dict[str, Dict[str, Any]] = {}        # var -> {node_id, output_name}
-        self.instance_to_resource: Dict[str, Optional[str]] = {}     # 实例名 -> resource_name
-        self.node_id_counter: int = 0
-        self.registry = RegistryAdapter(device_registry or {})
-
-    # ---- helpers ----
-    def _new_node_id(self) -> int:
-        nid = self.node_id_counter
-        self.node_id_counter += 1
-        return nid
-
-    def _assign_targets(self, targets) -> List[str]:
-        names: List[str] = []
-        import ast
-        if isinstance(targets, ast.Tuple):
-            for elt in targets.elts:
-                if isinstance(elt, ast.Name):
-                    names.append(elt.id)
-        elif isinstance(targets, ast.Name):
-            names.append(targets.id)
-        return names
-
-    def _extract_device_instantiation(self, node) -> Optional[Tuple[str, str]]:
-        import ast
-        if not isinstance(node.value, ast.Call):
-            return None
-        callee = node.value.func
-        if isinstance(callee, ast.Name):
-            class_name = callee.id
-        elif isinstance(callee, ast.Attribute) and isinstance(callee.value, ast.Name):
-            class_name = callee.attr
-        else:
-            return None
-        if isinstance(node.targets[0], ast.Name):
-            instance = node.targets[0].id
-            return instance, class_name
-        return None
-
-    def _extract_call(self, call) -> Tuple[str, str, Dict[str, Any], str]:
-        import ast
-        owner_name, method_name, call_kind = "", "", "func"
-        if isinstance(call.func, ast.Attribute):
-            method_name = call.func.attr
-            if isinstance(call.func.value, ast.Name):
-                owner_name = call.func.value.id
-                call_kind = "instance" if owner_name in self.instance_to_resource else "class_or_module"
-            elif isinstance(call.func.value, ast.Attribute) and isinstance(call.func.value.value, ast.Name):
-                owner_name = call.func.value.attr
-                call_kind = "class_or_module"
-        elif isinstance(call.func, ast.Name):
-            method_name = call.func.id
-            call_kind = "func"
-
-        def pack(node):
-            if isinstance(node, ast.Name):
-                return {"type": "variable", "value": node.id}
-            if isinstance(node, ast.Constant):
-                return {"type": "constant", "value": node.value}
-            if isinstance(node, ast.Dict):
-                return {"type": "dict", "value": self._parse_dict(node)}
-            if isinstance(node, ast.List):
-                return {"type": "list", "value": self._parse_list(node)}
-            return {"type": "raw", "value": ast.unparse(node) if hasattr(ast, "unparse") else str(node)}
-
-        args: Dict[str, Any] = {}
-        pos: List[Any] = []
-        for a in call.args:
-            pos.append(pack(a))
-        for kw in call.keywords:
-            args[kw.arg] = pack(kw.value)
-        if pos:
-            args["_positional"] = pos
-        return owner_name, method_name, args, call_kind
-
-    def _parse_dict(self, node) -> Dict[str, Any]:
-        import ast
-        out: Dict[str, Any] = {}
-        for k, v in zip(node.keys, node.values):
-            if isinstance(k, ast.Constant):
-                key = str(k.value)
-                if isinstance(v, ast.Name):
-                    out[key] = f"var:{v.id}"
-                elif isinstance(v, ast.Constant):
-                    out[key] = v.value
-                elif isinstance(v, ast.Dict):
-                    out[key] = self._parse_dict(v)
-                elif isinstance(v, ast.List):
-                    out[key] = self._parse_list(v)
-        return out
-
-    def _parse_list(self, node) -> List[Any]:
-        import ast
-        out: List[Any] = []
-        for elt in node.elts:
-            if isinstance(elt, ast.Name):
-                out.append(f"var:{elt.id}")
-            elif isinstance(elt, ast.Constant):
-                out.append(elt.value)
-            elif isinstance(elt, ast.Dict):
-                out.append(self._parse_dict(elt))
-            elif isinstance(elt, ast.List):
-                out.append(self._parse_list(elt))
-        return out
-
-    def _normalize_var_tokens(self, x: Any) -> Any:
-        if isinstance(x, str) and x.startswith("var:"):
-            return {"__var__": x[4:]}
-        if isinstance(x, list):
-            return [self._normalize_var_tokens(i) for i in x]
-        if isinstance(x, dict):
-            return {k: self._normalize_var_tokens(v) for k, v in x.items()}
-        return x
-
-    def _make_params_payload(self, resource_name: Optional[str], template_name: str, call_args: Dict[str, Any]) -> Dict[str, Any]:
-        input_keys = self.registry.get_action_input_keys(resource_name, template_name) if resource_name else []
-        defaults = self.registry.get_action_goal_default(resource_name, template_name) if resource_name else {}
-        params: Dict[str, Any] = dict(defaults)
-
-        def unpack(p):
-            t, v = p.get("type"), p.get("value")
-            if t == "variable":
-                return {"__var__": v}
-            if t == "dict":
-                return self._normalize_var_tokens(v)
-            if t == "list":
-                return self._normalize_var_tokens(v)
-            return v
-
-        for k, p in call_args.items():
-            if k == "_positional":
-                continue
-            params[k] = unpack(p)
-
-        pos = call_args.get("_positional", [])
-        if pos:
-            if input_keys:
-                for i, p in enumerate(pos):
-                    if i >= len(input_keys):
-                        break
-                    name = input_keys[i]
-                    if name in params:
-                        continue
-                    params[name] = unpack(p)
-            else:
-                for i, p in enumerate(pos):
-                    params[f"arg_{i}"] = unpack(p)
-        return params
-
-    # ---- handlers ----
-    def _on_assign(self, stmt):
-        import ast
-        inst = self._extract_device_instantiation(stmt)
-        if inst:
-            instance, code_class = inst
-            resource_name = self.registry.resolve_resource_by_classname(code_class)
-            self.instance_to_resource[instance] = resource_name
-            return
-
-        if isinstance(stmt.value, ast.Call):
-            owner, method, call_args, kind = self._extract_call(stmt.value)
-            if kind == "instance":
-                device_key = owner
-                resource_name = self.instance_to_resource.get(owner)
-            else:
-                device_key = owner
-                resource_name = self.registry.resolve_resource_by_classname(owner)
-
-            module = self.registry.get_device_module(resource_name)
-            params = self._make_params_payload(resource_name, method, call_args)
-
-            nid = self._new_node_id()
-            self.graph.add_workflow_node(
-                nid,
-                device_key=device_key,
-                resource_name=resource_name,      # ✅
-                module=module,
-                template_name=method,             # ✅
-                params=params,
-                variable_sources=self.variable_sources,
-                add_ready_if_no_vars=True,
-                prev_node_id=(nid - 1) if nid > 0 else None,
-            )
-
-            out_vars = self._assign_targets(stmt.targets[0])
-            for var in out_vars:
-                self.variable_sources[var] = {"node_id": nid, "output_name": "result"}
-
-    def _on_expr(self, stmt):
-        import ast
-        if not isinstance(stmt.value, ast.Call):
-            return
-        owner, method, call_args, kind = self._extract_call(stmt.value)
-        if kind == "instance":
-            device_key = owner
-            resource_name = self.instance_to_resource.get(owner)
-        else:
-            device_key = owner
-            resource_name = self.registry.resolve_resource_by_classname(owner)
-
-        module = self.registry.get_device_module(resource_name)
-        params = self._make_params_payload(resource_name, method, call_args)
-
-        nid = self._new_node_id()
-        self.graph.add_workflow_node(
-            nid,
-            device_key=device_key,
-            resource_name=resource_name,      # ✅
-            module=module,
-            template_name=method,             # ✅
-            params=params,
-            variable_sources=self.variable_sources,
-            add_ready_if_no_vars=True,
-            prev_node_id=(nid - 1) if nid > 0 else None,
-        )
-
-    def convert(self, python_code: str):
-        tree = ast.parse(python_code)
-        for stmt in tree.body:
-            if isinstance(stmt, ast.Assign):
-                self._on_assign(stmt)
-            elif isinstance(stmt, ast.Expr):
-                self._on_expr(stmt)
-        return self
--- a/unilabos/workflow/from_xdl.py
+++ b/unilabos/workflow/from_xdl.py
@@ -1,131 +0,0 @@
-from typing import List, Any, Dict
-import xml.etree.ElementTree as ET
-
-
-def convert_to_type(val: str) -> Any:
-    """将字符串值转换为适当的数据类型"""
-    if val == "True":
-        return True
-    if val == "False":
-        return False
-    if val == "?":
-        return None
-    if val.endswith(" g"):
-        return float(val.split(" ")[0])
-    if val.endswith("mg"):
-        return float(val.split("mg")[0])
-    elif val.endswith("mmol"):
-        return float(val.split("mmol")[0]) / 1000
-    elif val.endswith("mol"):
-        return float(val.split("mol")[0])
-    elif val.endswith("ml"):
-        return float(val.split("ml")[0])
-    elif val.endswith("RPM"):
-        return float(val.split("RPM")[0])
-    elif val.endswith(" °C"):
-        return float(val.split(" ")[0])
-    elif val.endswith(" %"):
-        return float(val.split(" ")[0])
-    return val
-
-
-def flatten_xdl_procedure(procedure_elem: ET.Element) -> List[ET.Element]:
-    """展平嵌套的XDL程序结构"""
-    flattened_operations = []
-    TEMP_UNSUPPORTED_PROTOCOL = ["Purge", "Wait", "Stir", "ResetHandling"]
-
-    def extract_operations(element: ET.Element):
-        if element.tag not in ["Prep", "Reaction", "Workup", "Purification", "Procedure"]:
-            if element.tag not in TEMP_UNSUPPORTED_PROTOCOL:
-                flattened_operations.append(element)
-
-        for child in element:
-            extract_operations(child)
-
-    for child in procedure_elem:
-        extract_operations(child)
-
-    return flattened_operations
-
-
-def parse_xdl_content(xdl_content: str) -> tuple:
-    """解析XDL内容"""
-    try:
-        xdl_content_cleaned = "".join(c for c in xdl_content if c.isprintable())
-        root = ET.fromstring(xdl_content_cleaned)
-
-        synthesis_elem = root.find("Synthesis")
-        if synthesis_elem is None:
-            return None, None, None
-
-        # 解析硬件组件
-        hardware_elem = synthesis_elem.find("Hardware")
-        hardware = []
-        if hardware_elem is not None:
-            hardware = [{"id": c.get("id"), "type": c.get("type")} for c in hardware_elem.findall("Component")]
-
-        # 解析试剂
-        reagents_elem = synthesis_elem.find("Reagents")
-        reagents = []
-        if reagents_elem is not None:
-            reagents = [{"name": r.get("name"), "role": r.get("role", "")} for r in reagents_elem.findall("Reagent")]
-
-        # 解析程序
-        procedure_elem = synthesis_elem.find("Procedure")
-        if procedure_elem is None:
-            return None, None, None
-
-        flattened_operations = flatten_xdl_procedure(procedure_elem)
-        return hardware, reagents, flattened_operations
-
-    except ET.ParseError as e:
-        raise ValueError(f"Invalid XDL format: {e}")
-
-
-def convert_xdl_to_dict(xdl_content: str) -> Dict[str, Any]:
-    """
-    将XDL XML格式转换为标准的字典格式
-
-    Args:
-        xdl_content: XDL XML内容
-
-    Returns:
-        转换结果，包含步骤和器材信息
-    """
-    try:
-        hardware, reagents, flattened_operations = parse_xdl_content(xdl_content)
-        if hardware is None:
-            return {"error": "Failed to parse XDL content", "success": False}
-
-        # 将XDL元素转换为字典格式
-        steps_data = []
-        for elem in flattened_operations:
-            # 转换参数类型
-            parameters = {}
-            for key, val in elem.attrib.items():
-                converted_val = convert_to_type(val)
-                if converted_val is not None:
-                    parameters[key] = converted_val
-
-            step_dict = {
-                "operation": elem.tag,
-                "parameters": parameters,
-                "description": elem.get("purpose", f"Operation: {elem.tag}"),
-            }
-            steps_data.append(step_dict)
-
-        # 合并硬件和试剂为统一的labware_info格式
-        labware_data = []
-        labware_data.extend({"id": hw["id"], "type": "hardware", **hw} for hw in hardware)
-        labware_data.extend({"name": reagent["name"], "type": "reagent", **reagent} for reagent in reagents)
-
-        return {
-            "success": True,
-            "steps": steps_data,
-            "labware": labware_data,
-            "message": f"Successfully converted XDL to dict format. Found {len(steps_data)} steps and {len(labware_data)} labware items.",
-        }
-
-    except Exception as e:
-        error_msg = f"XDL conversion failed: {str(e)}"
-        return {"error": error_msg, "success": False}
--- a/unilabos_msgs/package.xml
+++ b/unilabos_msgs/package.xml
@@ -2,7 +2,7 @@
 <?xml-model href="http://download.ros.org/schema/package_format3.xsd" schematypens="http://www.w3.org/2001/XMLSchema"?>
 <package format="3">
  <name>unilabos_msgs</name>
-  <version>0.11.3</version>
+  <version>0.11.2</version>
  <description>ROS2 Messages package for unilabos devices</description>
  <maintainer email="changjh@pku.edu.cn">Junhan Chang</maintainer>
  <maintainer email="18435084+Xuwznln@users.noreply.github.com">Xuwznln</maintainer>